Cell-free dna for assessing and/or treating cancer

ABSTRACT

This document relates to methods and materials for assessed, monitored, and/or treated mammals (e.g., humans) having cancer. For example, methods and materials for identifying a mammal as having cancer (e.g., a localized cancer) are provided. For example, methods and materials for assessing, monitoring, and/or treating a mammal having cancer are provided.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Patent Application Ser. No.62/673,516, filed on May 18, 2018, and claims the benefit of U.S. PatentApplication Ser. No. 62/795,900, filed on Jan. 23, 2019. The disclosureof the prior applications are considered part of (and are incorporatedby reference in) the disclosure of this application.

STATEMENT REGARDING FEDERAL FUNDING

This invention was made with U.S. government support under grant No.CA121113 from the National Institutes of Health. The U.S. government hascertain rights in the invention.

BACKGROUND I. Technical Field

This document relates to methods and materials for assessing and/ortreating mammals (e.g., humans) having cancer. For example, thisdocument provides methods and materials for identifying a mammal ashaving cancer (e.g., a localized cancer). For example, this documentprovides methods and materials for monitoring and/or treating a mammalhaving cancer.

2. Background Information

Much of the morbidity and mortality of human cancers world-wide is aresult of the late diagnosis of these diseases, where treatments areless effective (Torre et al., 2015 CA Cancer J Clin 65:87; and WorldHealth Organization, 2017 Guide to Cancer Early Diagnosis).Unfortunately, clinically proven biomarkers that can be used to broadlydiagnose and treat patients are not widely available (Mazzucchelli, 2000Advances in clinical pathology 4:111; Ruibal Morell, 1992 TheInternational journal of biological markers 7:160; Galli et al., 2013Clinical chemistry and laboratory medicine 51:1369; Sikaris, 2011 Heart,lung &circulation 20:634; Lin et al., 2016 in Screening for ColorectalCancer: A Systematic Review for the U.S. Preventive Services Task Force.(Rockville, Md.); Wanebo et al., 1978 N Engl J Med 299:448; and Zauber,2015 Dig Dis Sci 60:681).

SUMMARY

Recent analyses of cell-free DNA suggests that such approaches mayprovide new avenues for early diagnosis (Phallen et al., 2017 Sci TranslMed 9; Cohen et al., 2018 Science 359:926; Alix-Panabieres et al., 2016Cancer discovery 6:479; Siravegna et al., 2017 Nature reviews. Clinicaloncology 14:531; Haber et al., 2014 Cancer discovery 4:650; Husain etal., 2017 JAMA 318:1272; and Wan et al., 2017 Nat Rev Cancer 17:223).

This document provides methods and materials for determining a cell freeDNA (cfDNA) fragmentation profile in a mammal (e.g., in a sampleobtained from a mammal). In some cases, determining a cfDNAfragmentation profile in a mammal can be used for identifying a mammalas having cancer. For example, cfDNA fragments obtained from a mammal(e.g., from a sample obtained from a mammal) can be subjected to lowcoverage whole-genome sequencing, and the sequenced fragments can bemapped to the genome (e.g., in non-overlapping windows) and assessed todetermine a cfDNA fragmentation profile. This document also providesmethods and materials for assessing and/or treating mammals (e.g.,humans) having, or suspected of having, cancer. In some cases, thisdocument provides methods and materials for identifying a mammal ashaving cancer. For example, a sample (e.g., a blood sample) obtainedfrom a mammal can be assessed to determine if the mammal has cancerbased, at least in part, on the cfDNA fragmentation profile. In somecases, this document provides methods and materials for monitoringand/or treating a mammal having cancer. For example, one or more cancertreatments can be administered to a mammal identified as having cancer(e.g., based, at least in part, on a cfDNA fragmentation profile) totreat the mammal.

Described herein is a non-invasive method for the early detection andlocalization of cancer. cfDNA in the blood can provide a non-invasivediagnostic avenue for patients with cancer. As demonstrated herein, DNAEvaluation of Fragments for early Interception (DELFI) was developed andused to evaluate genome-wide fragmentation patterns of cfDNA of 236patients with breast, colorectal, lung, ovarian, pancreatic, gastric, orbile duct cancers as well as 245 healthy individuals. These analysesrevealed that cfDNA profiles of healthy individuals reflectednucleosomal fragmentation patterns of white blood cells, while patientswith cancer had altered fragmentation profiles. DELFI had sensitivitiesof detection ranging from 57% to >99% among the seven cancer types at98% specificity and identified the tissue of origin of the cancers to alimited number of sites in 75% of cases. Assessing cfDNA (e.g., usingDELFI) can provide a screening approach for early detection of cancer,which can increase the chance for successful treatment of a patienthaving cancer. Assessing cfDNA (e.g., using DELFI) can also provide anapproach for monitoring cancer, which can increase the chance forsuccessful treatment and improved outcome of a patient having cancer. Inaddition, a cfDNA fragmentation profile can be obtained from limitedamounts of cfDNA and using inexpensive reagents and/or instruments.

In general, one aspect of this document features methods for determininga cfDNA fragmentation profile of a mammal. The methods can include, orconsist essentially of, processing cfDNA fragments obtained from asample obtained from the mammal into sequencing libraries, subjectingthe sequencing libraries to whole genome sequencing (e.g., low-coveragewhole genome sequencing) to obtain sequenced fragments, mapping thesequenced fragments to a genome to obtain windows of mapped sequences,and analyzing the windows of mapped sequences to determine cfDNAfragment lengths. The mapped sequences can include tens to thousands ofwindows. The windows of mapped sequences can be non-overlapping windows.The windows of mapped sequences can each include about 5 million basepairs. The cfDNA fragmentation profile can be determined within eachwindow. The cfDNA fragmentation profile can include a median fragmentsize. The cfDNA fragmentation profile can include a fragment sizedistribution. The cfDNA fragmentation profile can include a ratio ofsmall cfDNA fragments to large cfDNA fragments in the windows of mappedsequences. The cfDNA fragmentation profile can be over the whole genome.The cfDNA fragmentation profile can be over a subgenomic interval (e.g.,an interval in a portion of a chromosome).

In another aspect, this document features methods for identifying amammal as having cancer. The methods can include, or consist essentiallyof, determining a cfDNA fragmentation profile in a sample obtained froma mammal, comparing the cfDNA fragmentation profile to a reference cfDNAfragmentation profile, and identifying the mammal as having cancer whenthe cfDNA fragmentation profile in the sample obtained from the mammalis different from the reference cfDNA fragmentation profile. Thereference cfDNA fragmentation profile can be a cfDNA fragmentationprofile of a healthy mammal. The reference cfDNA fragmentation profilecan be generated by determining a cfDNA fragmentation profile in asample obtained from the healthy mammal. The reference DNA fragmentationpattern can be a reference nucleosome cfDNA fragmentation profile. ThecfDNA fragmentation profiles can include a median fragment size, and amedian fragment size of the cfDNA fragmentation profile can be shorterthan a median fragment size of the reference cfDNA fragmentationprofile. The cfDNA fragmentation profiles can include a fragment sizedistribution, and a fragment size distribution of the cfDNAfragmentation profile can differ by at least 10 nucleotides as comparedto a fragment size distribution of the reference cfDNA fragmentationprofile. The cfDNA fragmentation profiles can include position dependentdifferences in fragmentation patterns, including a ratio of small cfDNAfragments to large cfDNA fragments, where a small cfDNA fragment can be100 base pairs (bp) to 150 bp in length and a large cfDNA fragments canbe 151 bp to 220 bp in length, and where a correlation of fragmentratios in the cfDNA fragmentation profile can be lower than acorrelation of fragment ratios of the reference cfDNA fragmentationprofile. The cfDNA fragmentation profiles can include sequence coverageof small cfDNA fragments, large cfDNA fragments, or of both small andlarge cfDNA fragments, across the genome. The cancer can be colorectalcancer, lung cancer, breast cancer, bile duct cancer, pancreatic cancer,gastric cancer, or ovarian cancer. The step of comparing can includecomparing the cfDNA fragmentation profile to a reference cfDNAfragmentation profile in windows across the whole genome. The step ofcomparing can include comparing the cfDNA fragmentation profile to areference cfDNA fragmentation profile over a subgenomic interval (e.g.,an interval in a portion of a chromosome). The mammal can have beenpreviously administered a cancer treatment to treat the cancer. Thecancer treatment can be surgery, adjuvant chemotherapy, neoadjuvantchemotherapy, radiation therapy, hormone therapy, cytotoxic therapy,immunotherapy, adoptive T cell therapy, targeted therapy, or anycombinations thereof. The method also can include administering to themammal a cancer treatment (e.g., surgery, adjuvant chemotherapy,neoadjuvant chemotherapy, radiation therapy, hormone therapy, cytotoxictherapy, immunotherapy, adoptive T cell therapy, targeted therapy, orany combinations thereof). The mammal can be monitored for the presenceof cancer after administration of the cancer treatment.

In another aspect, this document features methods for treating a mammalhaving cancer. The methods can include, or consist essentially of,identifying the mammal as having cancer, where the identifying includesdetermining a cfDNA fragmentation profile in a sample obtained from themammal, comparing the cfDNA fragmentation profile to a reference cfDNAfragmentation profile, and identifying the mammal as having cancer whenthe cfDNA fragmentation profile obtained from the mammal is differentfrom the reference cfDNA fragmentation profile; and administering acancer treatment to the mammal. The mammal can be a human. The cancercan be colorectal cancer, lung cancer, breast cancer, gastric cancers,pancreatic cancers, bile duct cancers, or ovarian cancer. The cancertreatment can be surgery, adjuvant chemotherapy, neoadjuvantchemotherapy, radiation therapy, hormone therapy, cytotoxic therapy,immunotherapy, adoptive T cell therapy, targeted therapy, orcombinations thereof. The reference cfDNA fragmentation profile can be acfDNA fragmentation profile of a healthy mammal. The reference cfDNAfragmentation profile can be generated by determining a cfDNAfragmentation profile in a sample obtained from a healthy mammal. Thereference DNA fragmentation pattern can be a reference nucleosome cfDNAfragmentation profile. The cfDNA fragmentation profile can include amedian fragment size, where a median fragment size of the cfDNAfragmentation profile is shorter than a median fragment size of thereference cfDNA fragmentation profile. The cfDNA fragmentation profilecan include a fragment size distribution, where a fragment sizedistribution of the cfDNA fragmentation profile differs by at least 10nucleotides as compared to a fragment size distribution of the referencecfDNA fragmentation profile. The cfDNA fragmentation profile can includea ratio of small cfDNA fragments to large cfDNA fragments in the windowsof mapped sequences, where a small cfDNA fragment is 100 bp to 150 bp inlength, where a large cfDNA fragments is 151 bp to 220 bp in length, andwhere a correlation of fragment ratios in the cfDNA fragmentationprofile is lower than a correlation of fragment ratios of the referencecfDNA fragmentation profile. The cfDNA fragmentation profile can includethe sequence coverage of small cfDNA fragments in windows across thegenome. The cfDNA fragmentation profile can include the sequencecoverage of large cfDNA fragments in windows across the genome. ThecfDNA fragmentation profile can include the sequence coverage of smalland large cfDNA fragments in windows across the genome. The step ofcomparing can include comparing the cfDNA fragmentation profile to areference cfDNA fragmentation profile over the whole genome. The step ofcomparing can include comparing the cfDNA fragmentation profile to areference cfDNA fragmentation profile over a subgenomic interval. Themammal can have previously been administered a cancer treatment to treatthe cancer. The cancer treatment can be surgery, adjuvant chemotherapy,neoadjuvant chemotherapy, radiation therapy, hormone therapy, cytotoxictherapy, immunotherapy, adoptive T cell therapy, targeted therapy, orcombinations thereof. The method also can include monitoring the mammalfor the presence of cancer after administration of the cancer treatment.

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention pertains. Although methods and materialssimilar or equivalent to those described herein can be used to practicethe invention, suitable methods and materials are described below. Allpublications, patent applications, patents, and other referencesmentioned herein are incorporated by reference in their entirety. Incase of conflict, the present specification, including definitions, willcontrol. In addition, the materials, methods, and examples areillustrative only and not intended to be limiting.

The details of one or more embodiments of the invention are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the invention will be apparent from thedescription and drawings, and from the claims.

DESCRIPTION OF THE DRAWINGS

FIG. 1. Schematic of an exemplary DELFI approach. Blood is collectedfrom a cohort of healthy individuals and patients with cancer.Nucleosome protected cfDNA is extracted from the plasma fraction,processed into sequencing libraries, examined through whole genomesequencing, mapped to the genome, and analyzed to determine cfDNAfragment profiles in different windows across the genome. Machinelearning approaches are used to categorize individuals as healthy or ashaving cancer and to identify the tumor tissue of origin usinggenome-wide cfDNA fragmentation patterns.

FIG. 2. Simulations of non-invasive cancer detection based on number ofalterations analyzed and tumor-derived cfDNA fragment distributions.Monte Carlo simulations were performed using different numbers oftumor-specific alterations to evaluate the probability of detectingcancer alterations in cfDNA at the indicated fraction of tumor-derivedmolecules. The simulations were performed assuming an average of 2000genome equivalents of cfDNA and the requirement of five or moreobservations of any alteration. These analyses indicate that increasingthe number of tumor-specific alterations improves the sensitivity ofdetection of circulating tumor DNA.

FIG. 3. Tumor-derived cfDNA fragment distributions. Cumulative densityfunctions of cfDNA fragment lengths of 42 loci containing tumor-specificalterations from 30 patients with breast, colorectal, lung, or ovariancancer are shown with 95% confidence bands (blue). Lengths of mutantcfDNA fragments were significantly different in size compared towild-type cfDNA fragments (red) at these loci.

FIGS. 4A and 4B. Tumor-derived cfDNA GC content and fragment length. A,GC content was similar for mutated and non-mutated fragments. B, GCcontent was not correlated to fragment length.

FIG. 5. Germline cfDNA fragment distributions. Cumulative densityfunctions of fragment lengths of 44 loci containing germline alterations(non-tumor derived) from 38 patients with breast, colorectal, lung, orovarian cancer are shown with 95% confidence bands. Fragments withgermline mutations (blue) were comparable in length to wild-type cfDNAfragment lengths (red).

FIG. 6. Hematopoietic cfDNA fragment distributions. Cumulative densityfunctions of fragment lengths of 41 loci containing hematopoieticalterations (non-tumor derived) from 28 patients with breast,colorectal, lung, or ovarian cancer are shown with 95% confidence bands.After correction for multiple testing, there were no significantdifferences (α=0.05) in the size distributions of mutated hematopoieticctDNA fragments (blue) and wild-type cfDNA fragments (red).

FIGS. 7A-7F. cfDNA fragmentation profiles in healthy individuals andpatients with cancer. A, Genome-wide cfDNA fragmentation profiles(defined as the ratio of short to long fragments) from ˜9× whole genomesequencing are shown in 5 Mb bins for 30 healthy individuals (top) and 8lung cancer patients (bottom). B, An analysis of healthy cfDNA (top),lung cancer cfDNA (middle), and healthy lymphocyte (bottom)fragmentation profiles and lymphocyte profiles from chromosome 1 at 1 Mbresolution. The healthy lymphocyte profiles were scaled with a standarddeviation equal to that of the median healthy cfDNA profiles. HealthycfDNA patterns closely mirrored those in healthy lymphocytes while lungcancer cfDNA profiles were more varied and differed from both healthyand lymphocyte profiles. C, Smoothed median distances between adjacentnucleosome centered at zero using 100 kb bins from healthy cfDNA (top)and nuclease-digested healthy lymphocytes (middle) are depicted togetherwith the first eigenvector for the genome contact matrix obtainedthrough previously reported Hi-C analyses of lymphoblastoid cells(bottom). Healthy cfDNA nucleosome distances closely mirrored those innuclease-digested lymphocytes as well as those from lymphoblastoid Hi-Canalyses. cfDNA fragmentation profiles from healthy individuals (n=30)had high correlations while patients with lung cancer had lowercorrelations to median fragmentation profiles of lymphocytes (D),healthy cfDNA (E), and lymphocyte nucleosome (F) distances.

FIG. 8. Density of cfDNA fragment lengths in healthy individuals andpatients with lung cancer. cfDNA fragments lengths are shown for healthyindividuals (n=30, gray) and patients with lung cancer (n=8, blue).

FIGS. 9A and 9B. Subsampling of whole genome sequence data for analysisof cfDNA fragmentation profiles. A, High coverage (9×) whole-genomesequencing data were subsampled to 2×, 1×, 0.5×, 0.2×, and 0.1× foldcoverage. Mean centered genome-wide fragmentation profiles in 5 Mb binsfor 30 healthy individuals and 8 patients with lung cancer are depictedfor each subsampled fold coverage with median profiles shown in blue. B,Pearson correlation of subsampled profiles to initial profile at 9×coverage for healthy individuals and patients with lung cancer.

FIG. 10. cfDNA fragmentation profiles and sequence alterations duringtherapy. Detection and monitoring of cancer in serial blood draws fromNSCLC patients (n=19) undergoing treatment with targeted tyrosine kinaseinhibitors (black arrows) was performed using targeted sequencing (top)and genome-wide fragmentation profiles (bottom). For each case, thevertical axis of the lower panel displays −1 times the correlation ofeach sample to the median healthy cfDNA fragmentation profile. Errorbars depict confidence intervals from binomial tests for mutant allelefractions and confidence intervals calculated using Fishertransformation for genome-wide fragmentation profiles. Although theapproaches analyze different aspects of cfDNA (whole genome compared tospecific alterations) the targeted sequencing and fragmentation profileswere similar for patients responding to therapy as well as those withstable or progressive disease. As fragmentation profiles reflect bothgenomic and epigenomic alterations, while mutant allele fractions onlyreflect individual mutations, mutant allele fractions alone may notreflect the absolute level of correlation of fragmentation profiles tohealthy individuals.

FIGS. 11A-11C. cfDNA fragmentation profiles in healthy individuals andpatients with cancer. A, Fragmentation profiles (bottom) in the contextof tumor copy number changes (top) in a colorectal cancer patient whereparallel analyses of tumor tissue were performed. The distribution ofsegment means and integer copy numbers are shown at top right in theindicated colors. Altered fragmentation profiles were present in regionsof the genome that were copy neutral and were further affected inregions with copy number changes. B, GC adjusted fragmentation profilesfrom 1-2× whole genome sequencing for healthy individuals and patientswith cancer are depicted per cancer type using 5 Mb windows. The medianhealthy profile is indicated in black and the 98% confidence band isshown in gray. For patients with cancer, individual profiles are coloredbased on their correlation to the healthy median. C, Windows areindicated in orange if more than 10% of the cancer samples had afragment ratio more than three standard deviations from the medianhealthy fragment ratio. These analyses highlight the multitude ofposition dependent alterations across the genome in cfDNA of individualswith cancer.

FIGS. 12A and 12B. Profiles of cfDNA fragment lengths in copy neutralregions in healthy individuals and one patient with colorectal cancer.A, The fragmentation profile in 211 copy neutral windows in chromosomes1-6 for 25 randomly selected healthy individuals (gray). For a patientwith colorectal cancer (CGCRC291) with an estimated mutant allelefraction of 20%, the cancer fragment length profile was diluted to anapproximate 10% tumor contribution (blue). A and B, While the marginaldensities of the fragment profiles for the healthy samples and cancerpatient show substantial overlap (A, right), the fragmentation profilesare different as can be seen visualization of the fragmentation profiles(A, left) and by the separation of the colorectal cancer patient fromthe healthy samples in a principal component analysis (B).

FIGS. 13A and 13B. Genome-wide GC correction of cfDNA fragments. Toestimate and control for the effects of GC content on sequencingcoverage, coverage in non-overlapping 100 kb genomic windows wascalculated across the autosomes. For each window, the average GC of thealigned fragments was calculated. A, Loess smoothing of raw coverage(top row) for two randomly selected healthy subjects (CGPLH189 andCGPLH380) and two cancer patients (CGPLLU161 and CGPLBR24) withundetectable aneuploidy (PA score <2.35). After subtracting the averagecoverage predicted by the loess model, the residuals were resealed tothe median autosomal coverage (bottom row). As fragment length may alsoresult in coverage biases, this GC correction procedure was performedseparately for short (≤150 bp) and long (≥151 bp) fragments. While the100 kb bins on chromosome 19 (blue points) consistently have lesscoverage than predicted by the loess model, we did not implement achromosome-specific correction as such an approach would remove theeffects of chromosomal copy number on coverage. B, Overall, a limitedcorrelation was found between short or long fragment coverage and GCcontent after correction among healthy subjects and cancer patients witha PA score <3.

FIG. 14. Schematic of machine learning model. Gradient tree boostingmachine learning was used to examine whether cfDNA can be categorized ashaving characteristics of a cancer patient or healthy individual. Themachine learning model included fragmentation size and coveragecharacteristics in windows throughout the genome, as well as chromosomalarm and mitochondrial DNA copy numbers. A 10-fold cross validationapproach was employed in which each sample is randomly assigned to afold and 9 of the folds (90% of the data) are used for training and onefold (10% of the data) is used for testing. The prediction accuracy froma single cross validation is an average over the 10 possiblecombinations of test and training sets. As this prediction accuracy canreflect bias from the initial randomization of patients, the entireprocedure was repeat, including the randomization of patients to folds,10 times. For all cases, feature selection and model estimation wereperformed on training data and were validated on test data and the testdata were never used for feature selection. Ultimately, a DELFI scorewas obtained that could be used to classify individuals as likelyhealthy or having cancer.

FIG. 15. Distribution of AUCs across the repeated 10-foldcross-validation. The 25^(th), 50^(th), and 75^(th) percentiles of the100 AUCs for the cohort of 215 healthy individuals and 208 patients withcancer are indicated by dashed lines.

FIGS. 16A and 16B. Whole-genome analyses of chromosomal arm copy numberchanges and mitochondrial genome representation. A, Z scores for eachautosome arm are depicted for healthy individuals (n=215) and patientswith cancer (n=208). The vertical axis depicts normal copy at zero withpositive and negative values indicating arm gains and losses,respectively. Z scores greater than 50 or less than −50 are thresholdedat the indicated values. B, The fraction of reads mapping to themitochondrial genome is depicted for healthy individuals and patientswith cancer.

FIGS. 17A and 17B. Detection of cancer using DELFI. A, Receiver operatorcharacteristics for detection of cancer using cfDNA fragmentationprofiles and other genome-wide features in a machine learning approachare depicted for a cohort of 215 healthy individuals and 208 patientswith cancer (DELFI, AUC=0.94), with ≥95% specificity shaded in blue.Machine learning analyses of chromosomal arm copy number (Chr copynumber (ML)), and mitochondrial genome copy number (mtDNA), are shown inthe indicated colors. B, Analyses of individual cancers types using theDELFI-combined approach had AUCs ranging from 0.86 to >0.99.

FIG. 18. DELFI detection of cancer by stage. Receiver operatorcharacteristics for detection of cancer using cfDNA fragmentationprofiles and other genome-wide features in a machine learning approachare depicted for a cohort of 215 healthy individuals and each stage of208 patients with cancer with >95% specificity shaded in blue.

FIG. 19. DELFI tissue of origin prediction. Receiver operatorcharacteristics for DELFI tissue prediction of bile duct, breast,colorectal, gastric, lung, ovarian, and pancreatic cancers are depicted.In order to increase sample sizes within cancer type classes, casesdetected with a 90% specificity were included, and the lung cancercohort was supplemented with the addition of baseline cfDNA data from 18lung cancer patients with prior treatment (see, e.g., Shen et al., 2018Nature, 563:579-583).

FIG. 20. Detection of cancer using DELFI and mutation-based cfDNAapproaches. DELFI (green) and targeted sequencing for mutationidentification (blue) were performed independently in a cohort of 126patients with breast, bile duct, colorectal, gastric, lung, or ovariancancers. The number of individuals detected by each approach and incombination are indicated for DELFI detection with a specificity of 98%,targeted sequencing specificity at >99%, and a combined specificity of98%. ND indicates not detected.

DETAILED DESCRIPTION

This document provides methods and materials for determining a cfDNAfragmentation profile in a mammal (e.g., in a sample obtained from amammal). As used herein, the terms “fragmentation profile,” “positiondependent differences in fragmentation patterns,” and “differences infragment size and coverage in a position dependent manner across thegenome” are equivalent and can be used interchangeably. In some cases,determining a cfDNA fragmentation profile in a mammal can be used foridentifying a mammal as having cancer. For example, cfDNA fragmentsobtained from a mammal (e.g., from a sample obtained from a mammal) canbe subjected to low coverage whole-genome sequencing, and the sequencedfragments can be mapped to the genome (e.g., in non-overlapping windows)and assessed to determine a cfDNA fragmentation profile. As describedherein, a cfDNA fragmentation profile of a mammal having cancer is moreheterogeneous (e.g., in fragment lengths) than a cfDNA fragmentationprofile of a healthy mammal (e.g., a mammal not having cancer). As such,this document also provides methods and materials for assessing,monitoring, and/or treating mammals (e.g., humans) having, or suspectedof having, cancer. In some cases, this document provides methods andmaterials for identifying a mammal as having cancer. For example, asample (e.g., a blood sample) obtained from a mammal can be assessed todetermine the presence and, optionally, the tissue of origin of thecancer in the mammal based, at least in part, on the cfDNA fragmentationprofile of the mammal. In some cases, this document provides methods andmaterials for monitoring a mammal as having cancer. For example, asample (e.g., a blood sample) obtained from a mammal can be assessed todetermine the presence of the cancer in the mammal based, at least inpart, on the cfDNA fragmentation profile of the mammal. In some cases,this document provides methods and materials for identifying a mammal ashaving cancer, and administering one or more cancer treatments to themammal to treat the mammal. For example, a sample (e.g., a blood sample)obtained from a mammal can be assessed to determine if the mammal hascancer based, at least in part, on the cfDNA fragmentation profile ofthe mammal, and one or more cancer treatments can be administered to themammal.

A cfDNA fragmentation profile can include one or more cfDNAfragmentation patterns. A cfDNA fragmentation pattern can include anyappropriate cfDNA fragmentation pattern. Examples of cfDNA fragmentationpatterns include, without limitation, median fragment size, fragmentsize distribution, ratio of small cfDNA fragments to large cfDNAfragments, and the coverage of cfDNA fragments. In some cases, a cfDNAfragmentation pattern includes two or more (e.g., two, three, or four)of median fragment size, fragment size distribution, ratio of smallcfDNA fragments to large cfDNA fragments, and the coverage of cfDNAfragments. In some cases, cfDNA fragmentation profile can be agenome-wide cfDNA profile (e.g., a genome-wide cfDNA profile in windowsacross the genome). In some cases, cfDNA fragmentation profile can be atargeted region profile. A targeted region can be any appropriateportion of the genome (e.g., a chromosomal region). Examples ofchromosomal regions for which a cfDNA fragmentation profile can bedetermined as described herein include, without limitation, a portion ofa chromosome (e.g., a portion of 2q, 4p, 5p, 6q, 7p, 8q, 9q, 10q, 11q,12q, and/or 14q) and a chromosomal arm (e.g., a chromosomal arm of 8q,13q, 11q, and/or 3p). In some cases, a cfDNA fragmentation profile caninclude two or more targeted region profiles.

In some cases, a cfDNA fragmentation profile can be used to identifychanges (e.g., alterations) in cfDNA fragment lengths. An alteration canbe a genome-wide alteration or an alteration in one or more targetedregions/loci. A target region can be any region containing one or morecancer-specific alterations. Examples of cancer-specific alterations,and their chromosomal locations, include, without limitation, thoseshown in Table 3 (Appendix C) and those shown in Table 6 (Appendix F).In some cases, a cfDNA fragmentation profile can be used to identify(e.g., simultaneously identify) from about 10 alterations to about 500alterations (e.g., from about 25 to about 500, from about 50 to about500, from about 100 to about 500, from about 200 to about 500, fromabout 300 to about 500, from about 10 to about 400, from about 10 toabout 300, from about 10 to about 200, from about 10 to about 100, fromabout 10 to about 50, from about 20 to about 400, from about 30 to about300, from about 40 to about 200, from about 50 to about 100, from about20 to about 100, from about 25 to about 75, from about 50 to about 250,or from about 100 to about 200, alterations).

In some cases, a cfDNA fragmentation profile can be used to detecttumor-derived DNA. For example, a cfDNA fragmentation profile can beused to detect tumor-derived DNA by comparing a cfDNA fragmentationprofile of a mammal having, or suspected of having, cancer to areference cfDNA fragmentation profile (e.g., a cfDNA fragmentationprofile of a healthy mammal and/or a nucleosomal DNA fragmentationprofile of healthy cells from the mammal having, or suspected of having,cancer). In some cases, a reference cfDNA fragmentation profile is apreviously generated profile from a healthy mammal. For example, methodsprovided herein can be used to determine a reference cfDNA fragmentationprofile in a healthy mammal, and that reference cfDNA fragmentationprofile can be stored (e.g., in a computer or other electronic storagemedium) for future comparison to a test cfDNA fragmentation profile inmammal having, or suspected of having, cancer. In some cases, areference cfDNA fragmentation profile (e.g., a stored cfDNAfragmentation profile) of a healthy mammal is determined over the wholegenome. In some cases, a reference cfDNA fragmentation profile (e.g., astored cfDNA fragmentation profile) of a healthy mammal is determinedover a subgenomic interval.

In some cases, a cfDNA fragmentation profile can be used to identify amammal (e.g., a human) as having cancer (e.g., a colorectal cancer, alung cancer, a breast cancer, a gastric cancer, a pancreatic cancer, abile duct cancer, and/or an ovarian cancer).

A cfDNA fragmentation profile can include a cfDNA fragment size pattern.cfDNA fragments can be any appropriate size. For example, cfDNA fragmentcan be from about 50 base pairs (bp) to about 400 bp in length. Asdescribed herein, a mammal having cancer can have a cfDNA fragment sizepattern that contains a shorter median cfDNA fragment size than themedian cfDNA fragment size in a healthy mammal. A healthy mammal (e.g.,a mammal not having cancer) can have cfDNA fragment sizes having amedian cfDNA fragment size from about 166.6 bp to about 167.2 bp (e.g.,about 166.9 bp). In some cases, a mammal having cancer can have cfDNAfragment sizes that are, on average, about 1.28 bp to about 2.49 bp(e.g., about 1.88 bp) shorter than cfDNA fragment sizes in a healthymammal. For example, a mammal having cancer can have cfDNA fragmentsizes having a median cfDNA fragment size of about 164.11 bp to about165.92 bp (e.g., about 165.02 bp).

A cfDNA fragmentation profile can include a cfDNA fragment sizedistribution. As described herein, a mammal having cancer can have acfDNA size distribution that is more variable than a cfDNA fragment sizedistribution in a healthy mammal. In some case, a size distribution canbe within a targeted region. A healthy mammal (e.g., a mammal not havingcancer) can have a targeted region cfDNA fragment size distribution ofabout 1 or less than about 1. In some cases, a mammal having cancer canhave a targeted region cfDNA fragment size distribution that is longer(e.g., 10, 15, 20, 25, 30, 35, 40, 45, 50 or more bp longer, or anynumber of base pairs between these numbers) than a targeted region cfDNAfragment size distribution in a healthy mammal. In some cases, a mammalhaving cancer can have a targeted region cfDNA fragment sizedistribution that is shorter (e.g., 10, 15, 20, 25, 30, 35, 40, 45, 50or more bp shorter, or any number of base pairs between these numbers)than a targeted region cfDNA fragment size distribution in a healthymammal. In some cases, a mammal having cancer can have a targeted regioncfDNA fragment size distribution that is about 47 bp smaller to about 30bp longer than a targeted region cfDNA fragment size distribution in ahealthy mammal. In some cases, a mammal having cancer can have atargeted region cfDNA fragment size distribution of, on average, a 10,11, 12, 13, 14, 15, 15, 17, 18, 19, 20 or more bp difference in lengthsof cfDNA fragments. For example, a mammal having cancer can have atargeted region cfDNA fragment size distribution of, on average, about a13 bp difference in lengths of cfDNA fragments. In some case, a sizedistribution can be a genome-wide size distribution. A healthy mammal(e.g., a mammal not having cancer) can have very similar distributionsof short and long cfDNA fragments genome-wide. In some cases, a mammalhaving cancer can have, genome-wide, one or more alterations (e.g.,increases and decreases) in cfDNA fragment sizes. The one or morealterations can be any appropriate chromosomal region of the genome. Forexample, an alteration can be in a portion of a chromosome. Examples ofportions of chromosomes that can contain one or more alterations incfDNA fragment sizes include, without limitation, portions of 2q, 4p,5p, 6q, 7p, 8q, 9q, 10q, 11q, 12q, and 14q. For example, an alterationcan be across a chromosome arm (e.g., an entire chromosome arm).

A cfDNA fragmentation profile can include a ratio of small cfDNAfragments to large cfDNA fragments and a correlation of fragment ratiosto reference fragment ratios. As used herein, with respect to ratios ofsmall cfDNA fragments to large cfDNA fragments, a small cfDNA fragmentcan be from about 100 bp in length to about 150 bp in length. As usedherein, with respect to ratios of small cfDNA fragments to large cfDNAfragments, a large cfDNA fragment can be from about 151 bp in length to220 bp in length. As described herein, a mammal having cancer can have acorrelation of fragment ratios (e.g., a correlation of cfDNA fragmentratios to reference DNA fragment ratios such as DNA fragment ratios fromone or more healthy mammals) that is lower (e.g., 2-fold lower, 3-foldlower, 4-fold lower, 5-fold lower, 6-fold lower, 7-fold lower, 8-foldlower, 9-fold lower, 10-fold lower, or more) than in a healthy mammal. Ahealthy mammal (e.g., a mammal not having cancer) can have a correlationof fragment ratios (e.g., a correlation of cfDNA fragment ratios toreference DNA fragment ratios such as DNA fragment ratios from one ormore healthy mammals) of about 1 (e.g., about 0.96). In some cases, amammal having cancer can have a correlation of fragment ratios (e.g., acorrelation of cfDNA fragment ratios to reference DNA fragment ratiossuch as DNA fragment ratios from one or more healthy mammals) that is,on average, about 0.19 to about 0.30 (e.g., about 0.25) lower than acorrelation of fragment ratios (e.g., a correlation of cfDNA fragmentratios to reference DNA fragment ratios such as DNA fragment ratios fromone or more healthy mammals) in a healthy mammal.

A cfDNA fragmentation profile can include coverage of all fragments.Coverage of all fragments can include windows (e.g., non-overlappingwindows) of coverage. In some cases, coverage of all fragments caninclude windows of small fragments (e.g., fragments from about 100 bp toabout 150 bp in length). In some cases, coverage of all fragments caninclude windows of large fragments (e.g., fragments from about 151 bp toabout 220 bp in length).

In some cases, a cfDNA fragmentation profile can be used to identify thetissue of origin of a cancer (e.g., a colorectal cancer, a lung cancer,a breast cancer, a gastric cancer, a pancreatic cancer, a bile ductcancer, or an ovarian cancer). For example, a cfDNA fragmentationprofile can be used to identify a localized cancer. When a cfDNAfragmentation profile includes a targeted region profile, one or morealterations described herein (e.g., in Table 3 (Appendix C) and/or inTable 6 (Appendix F)) can be used to identify the tissue of origin of acancer. In some cases, one or more alterations in chromosomal regionscan be used to identify the tissue of origin of a cancer.

A cfDNA fragmentation profile can be obtained using any appropriatemethod. In some cases, cfDNA from a mammal (e.g., a mammal having, orsuspected of having, cancer) can be processed into sequencing librarieswhich can be subjected to whole genome sequencing (e.g., low-coveragewhole genome sequencing), mapped to the genome, and analyzed todetermine cfDNA fragment lengths. Mapped sequences can be analyzed innon-overlapping windows covering the genome. Windows can be anyappropriate size. For example, windows can be from thousands to millionsof bases in length. As one non-limiting example, a window can be about 5megabases (Mb) long. Any appropriate number of windows can be mapped.For example, tens to thousands of windows can be mapped in the genome.For example, hundreds to thousands of windows can be mapped in thegenome. A cfDNA fragmentation profile can be determined within eachwindow. In some cases, a cfDNA fragmentation profile can be obtained asdescribed in Example 1. In some cases, a cfDNA fragmentation profile canbe obtained as shown in FIG. 1.

In some cases, methods and materials described herein also can includemachine learning. For example, machine learning can be used foridentifying an altered fragmentation profile (e.g., using coverage ofcfDNA fragments, fragment size of cfDNA fragments, coverage ofchromosomes, and mtDNA).

In some cases, methods and materials described herein can be the solemethod used to identify a mammal (e.g., a human) as having cancer (e.g.,a colorectal cancer, a lung cancer, a breast cancer, a gastric cancer, apancreatic cancer, a bile duct cancer, and/or an ovarian cancer). Forexample, determining a cfDNA fragmentation profile can be the solemethod used to identify a mammal as having cancer.

In some cases, methods and materials described herein can be usedtogether with one or more additional methods used to identify a mammal(e.g., a human) as having cancer (e.g., a colorectal cancer, a lungcancer, a breast cancer, a gastric cancer, a pancreatic cancer, a bileduct cancer, and/or an ovarian cancer). Examples of methods used toidentify a mammal as having cancer include, without limitation,identifying one or more cancer-specific sequence alterations,identifying one or more chromosomal alterations (e.g., aneuploidies andrearrangements), and identifying other cfDNA alterations. For example,determining a cfDNA fragmentation profile can be used together withidentifying one or more cancer-specific mutations in a mammal's genometo identify a mammal as having cancer. For example, determining a cfDNAfragmentation profile can be used together with identifying one or moreaneuploidies in a mammal's genome to identify a mammal as having cancer.

In some aspects, this document also provides methods and materials forassessing, monitoring, and/or treating mammals (e.g., humans) having, orsuspected of having, cancer. In some cases, this document providesmethods and materials for identifying a mammal as having cancer. Forexample, a sample (e.g., a blood sample) obtained from a mammal can beassessed to determine if the mammal has cancer based, at least in part,on the cfDNA fragmentation profile of the mammal. In some cases, thisdocument provides methods and materials for identifying the location(e.g., the anatomic site or tissue of origin) of a cancer in a mammal.For example, a sample (e.g., a blood sample) obtained from a mammal canbe assessed to determine the tissue of origin of the cancer in themammal based, at least in part, on the cfDNA fragmentation profile ofthe mammal. In some cases, this document provides methods and materialsfor identifying a mammal as having cancer, and administering one or morecancer treatments to the mammal to treat the mammal. For example, asample (e.g., a blood sample) obtained from a mammal can be assessed todetermine if the mammal has cancer based, at least in part, on the cfDNAfragmentation profile of the mammal, and administering one or morecancer treatments to the mammal. In some cases, this document providesmethods and materials for treating a mammal having cancer. For example,one or more cancer treatments can be administered to a mammal identifiedas having cancer (e.g., based, at least in part, on the cfDNAfragmentation profile of the mammal) to treat the mammal. In some cases,during or after the course of a cancer treatment (e.g., any of thecancer treatments described herein), a mammal can undergo monitoring (orbe selected for increased monitoring) and/or further diagnostic testing.In some cases, monitoring can include assessing mammals having, orsuspected of having, cancer by, for example, assessing a sample (e.g., ablood sample) obtained from the mammal to determine the cfDNAfragmentation profile of the mammal as described herein, and changes inthe cfDNA fragmentation profiles over time can be used to identifyresponse to treatment and/or identify the mammal as having cancer (e.g.,a residual cancer).

Any appropriate mammal can be assessed, monitored, and/or treated asdescribed herein. A mammal can be a mammal having cancer. A mammal canbe a mammal suspected of having cancer. Examples of mammals that can beassessed, monitored, and/or treated as described herein include, withoutlimitation, humans, primates such as monkeys, dogs, cats, horses, cows,pigs, sheep, mice, and rats. For example, a human having, or suspectedof having, cancer can be assessed to determine a cfDNA fragmentationprofiled as described herein and, optionally, can be treated with one ormore cancer treatments as described herein.

Any appropriate sample from a mammal can be assessed as described herein(e.g., assessed for a DNA fragmentation pattern). In some cases, asample can include DNA (e.g., genomic DNA). In some cases, a sample caninclude cfDNA (e.g., circulating tumor DNA (ctDNA)). In some cases, asample can be fluid sample (e.g., a liquid biopsy). Examples of samplesthat can contain DNA and/or polypeptides include, without limitation,blood (e.g., whole blood, serum, or plasma), amnion, tissue, urine,cerebrospinal fluid, saliva, sputum, broncho-alveolar lavage, bile,lymphatic fluid, cyst fluid, stool, ascites, pap smears, breast milk,and exhaled breath condensate. For example, a plasma sample can beassessed to determine a cfDNA fragmentation profiled as describedherein.

A sample from a mammal to be assessed as described herein (e.g.,assessed for a DNA fragmentation pattern) can include any appropriateamount of cfDNA. In some cases, a sample can include a limited amount ofDNA. For example, a cfDNA fragmentation profile can be obtained from asample that includes less DNA than is typically required for other cfDNAanalysis methods, such as those described in, for example, Phallen etal., 2017 Sci Transl Med 9; Cohen et al., 2018 Science 359:926; Newmanet al., 2014 Nat Med 20:548; and Newman et al., 2016 Nat Biotechnol34:547).

In some cases, a sample can be processed (e.g., to isolate and/or purifyDNA and/or polypeptides from the sample). For example, DNA isolationand/or purification can include cell lysis (e.g., using detergentsand/or surfactants), protein removal (e.g., using a protease), and/orRNA removal (e.g., using an RNase). As another example, polypeptideisolation and/or purification can include cell lysis (e.g., usingdetergents and/or surfactants), DNA removal (e.g., using a DNase),and/or RNA removal (e.g., using an RNase).

A mammal having, or suspected of having, any appropriate type of cancercan be assessed (e.g., to determine a cfDNA fragmentation profile)and/or treated (e.g., by administering one or more cancer treatments tothe mammal) using the methods and materials described herein. A cancercan be any stage cancer. In some cases, a cancer can be an early stagecancer. In some cases, a cancer can be an asymptomatic cancer. In somecases, a cancer can be a residual disease and/or a recurrence (e.g.,after surgical resection and/or after cancer therapy). A cancer can beany type of cancer. Examples of types of cancers that can be assessed,monitored, and/or treated as described herein include, withoutlimitation, colorectal cancers, lung cancers, breast cancers, gastriccancers, pancreatic cancers, bile duct cancers, and ovarian cancers.

When treating a mammal having, or suspected of having, cancer asdescribed herein, the mammal can be administered one or more cancertreatments. A cancer treatment can be any appropriate cancer treatment.One or more cancer treatments described herein can be administered to amammal at any appropriate frequency (e.g., once or multiple times over aperiod of time ranging from days to weeks). Examples of cancertreatments include, without limitation adjuvant chemotherapy,neoadjuvant chemotherapy, radiation therapy, hormone therapy, cytotoxictherapy, immunotherapy, adoptive T cell therapy (e.g., chimeric antigenreceptors and/or T cells having wild-type or modified T cell receptors),targeted therapy such as administration of kinase inhibitors (e.g.,kinase inhibitors that target a particular genetic lesion, such as atranslocation or mutation), (e.g. a kinase inhibitor, an antibody, abispecific antibody), signal transduction inhibitors, bispecificantibodies or antibody fragments (e.g., BiTEs), monoclonal antibodies,immune checkpoint inhibitors, surgery (e.g., surgical resection), or anycombination of the above. In some cases, a cancer treatment can reducethe severity of the cancer, reduce a symptom of the cancer, and/or toreduce the number of cancer cells present within the mammal.

In some cases, a cancer treatment can include an immune checkpointinhibitor. Non-limiting examples of immune checkpoint inhibitors includenivolumab (Opdivo), pembrolizumab (Keytruda), atezolizumab (tecentriq),avelumab (bavencio), durvalumab (imfinzi), ipilimumab (yervoy). See,e.g., Pardoll (2012) Nat. Rev Cancer 12: 252-264; Sun et al. (2017) EurRev Med Pharmacol Sci 21(6): 1198-1205; Hamanishi et al. (2015) J. Clin.Oncol. 33(34): 4015-22; Brahmer et al. (2012) N Engl J Med 366(26):2455-65; Ricciuti et al. (2017) J. Thorac Oncol. 12(5): e51-e55; Elliset al. (2017) Clin Lung Cancer pii: S1525-7304(17)30043-8; Zou and Awad(2017) Ann Oncol 28(4): 685-687; Sorscher (2017) N Engl J Med 376(10:996-7; Hui et al. (2017) Ann Oncol 28(4): 874-881; Vansteenkiste et al.(2017) Expert Opin Biol Ther 17(6): 781-789; Hellmann et al. (2017)Lancet Oncol. 18(1): 31-41, Chen (2017) J. Chin Med Assoc 80(1): 7-14.

In some cases, a cancer treatment can be an adoptive T cell therapy(e.g., chimeric antigen receptors and/or T cells having wild-type ormodified T cell receptors). See, e.g., Rosenberg and Restifo (2015)Science 348(6230): 62-68; Chang and Chen (2017) Trends Mol Med 23(5):430-450; Yee and Lizee (2016) Cancer J. 23(2): 144-148; Chen et al.(2016) Oncoimmunology 6(2): e1273302; US 2016/0194404; US 2014/0050788;US 2014/0271635; U.S. Pat. No. 9,233,125; incorporated by reference intheir entirety herein.

In some cases, a cancer treatment can be a chemotherapeutic agent.Non-limiting examples of chemotherapeutic agents include: amsacrine,azacitidine, axathioprine, bevacizumab (or an antigen-binding fragmentthereof), bleomycin, busulfan, carboplatin, capecitabine, chlorambucil,cisplatin, cyclophosphamide, cytarabine, dacarbazine, daunorubicin,docetaxel, doxifluridine, doxorubicin, epirubicin, erlotinibhydrochlorides, etoposide, fiudarabine, floxuridine, fludarabine,fluorouracil, gemcitabine, hydroxyurea, idarubicin, ifosfamide,irinotecan, lomustine, mechlorethamine, melphalan, mercaptopurine,methotrxate, mitomycin, mitoxantrone, oxaliplatin, paclitaxel,pemetrexed, procarbazine, all-trans retinoic acid, streptozocin,tafluposide, temozolomide, teniposide, tioguanine, topotecan,uramustine, valrubicin, vinblastine, vincristine, vindesine,vinorelbine, and combinations thereof. Additional examples ofanti-cancer therapies are known in the art; see, e.g. the guidelines fortherapy from the American Society of Clinical Oncology (ASCO), EuropeanSociety for Medical Oncology (ESMO), or National Comprehensive CancerNetwork (NCCN).

When monitoring a mammal having, or suspected of having, cancer asdescribed herein (e.g., based, at least in part, on the cfDNAfragmentation profile of the mammal), the monitoring can be before,during, and/or after the course of a cancer treatment. Methods ofmonitoring provided herein can be used to determine the efficacy of oneor more cancer treatments and/or to select a mammal for increasedmonitoring. In some cases, the monitoring can include identifying acfDNA fragmentation profile as described herein. For example, a cfDNAfragmentation profile can be obtained before administering one or morecancer treatments to a mammal having, or suspected or having, cancer,one or more cancer treatments can be administered to the mammal, and oneor more cfDNA fragmentation profiles can be obtained during the courseof the cancer treatment. In some cases, a cfDNA fragmentation profilecan change during the course of cancer treatment (e.g., any of thecancer treatments described herein). For example, a cfDNA fragmentationprofile indicative that the mammal has cancer can change to a cfDNAfragmentation profile indicative that the mammal does not have cancer.Such a cfDNA fragmentation profile change can indicate that the cancertreatment is working. Conversely, a cfDNA fragmentation profile canremain static (e.g., the same or approximately the same) during thecourse of cancer treatment (e.g., any of the cancer treatments describedherein). Such a static cfDNA fragmentation profile can indicate that thecancer treatment is not working. In some cases, the monitoring caninclude conventional techniques capable of monitoring one or more cancertreatments (e.g., the efficacy of one or more cancer treatments). Insome cases, a mammal selected for increased monitoring can beadministered a diagnostic test (e.g., any of the diagnostic testsdisclosed herein) at an increased frequency compared to a mammal thathas not been selected for increased monitoring. For example, a mammalselected for increased monitoring can be administered a diagnostic testat a frequency of twice daily, daily, bi-weekly, weekly, bi-monthly,monthly, quarterly, semi-annually, annually, or any at frequencytherein. In some cases, a mammal selected for increased monitoring canbe administered a one or more additional diagnostic tests compared to amammal that has not been selected for increased monitoring. For example,a mammal selected for increased monitoring can be administered twodiagnostic tests, whereas a mammal that has not been selected forincreased monitoring is administered only a single diagnostic test (orno diagnostic tests). In some cases, a mammal that has been selected forincreased monitoring can also be selected for further diagnostictesting. Once the presence of a tumor or a cancer (e.g., a cancer cell)has been identified (e.g., by any of the variety of methods disclosedherein), it may be beneficial for the mammal to undergo both increasedmonitoring (e.g., to assess the progression of the tumor or cancer inthe mammal and/or to assess the development of one or more cancerbiomarkers such as mutations), and further diagnostic testing (e.g., todetermine the size and/or exact location (e.g., tissue of origin) of thetumor or the cancer). In some cases, one or more cancer treatments canbe administered to the mammal that is selected for increased monitoringafter a cancer biomarker is detected and/or after the cfDNAfragmentation profile of the mammal has not improved or deteriorated.Any of the cancer treatments disclosed herein or known in the art can beadministered. For example, a mammal that has been selected for increasedmonitoring can be further monitored, and a cancer treatment can beadministered if the presence of the cancer cell is maintained throughoutthe increased monitoring period. Additionally or alternatively, a mammalthat has been selected for increased monitoring can be administered acancer treatment, and further monitored as the cancer treatmentprogresses. In some cases, after a mammal that has been selected forincreased monitoring has been administered a cancer treatment, theincreased monitoring will reveal one or more cancer biomarkers (e.g.,mutations). In some cases, such one or more cancer biomarkers willprovide cause to administer a different cancer treatment (e.g., aresistance mutation may arise in a cancer cell during the cancertreatment, which cancer cell harboring the resistance mutation isresistant to the original cancer treatment).

When a mammal is identified as having cancer as described herein (e.g.,based, at least in part, on the cfDNA fragmentation profile of themammal), the identifying can be before and/or during the course of acancer treatment. Methods of identifying a mammal as having cancerprovided herein can be used as a first diagnosis to identify the mammal(e.g., as having cancer before any course of treatment) and/or to selectthe mammal for further diagnostic testing. In some cases, once a mammalhas been determined to have cancer, the mammal may be administeredfurther tests and/or selected for further diagnostic testing. In somecases, methods provided herein can be used to select a mammal forfurther diagnostic testing at a time period prior to the time periodwhen conventional techniques are capable of diagnosing the mammal withan early-stage cancer. For example, methods provided herein forselecting a mammal for further diagnostic testing can be used when amammal has not been diagnosed with cancer by conventional methods and/orwhen a mammal is not known to harbor a cancer. In some cases, a mammalselected for further diagnostic testing can be administered a diagnostictest (e.g., any of the diagnostic tests disclosed herein) at anincreased frequency compared to a mammal that has not been selected forfurther diagnostic testing. For example, a mammal selected for furtherdiagnostic testing can be administered a diagnostic test at a frequencyof twice daily, daily, bi-weekly, weekly, bi-monthly, monthly,quarterly, semi-annually, annually, or any at frequency therein. In somecases, a mammal selected for further diagnostic testing can beadministered a one or more additional diagnostic tests compared to amammal that has not been selected for further diagnostic testing. Forexample, a mammal selected for further diagnostic testing can beadministered two diagnostic tests, whereas a mammal that has not beenselected for further diagnostic testing is administered only a singlediagnostic test (or no diagnostic tests). In some cases, the diagnostictesting method can determine the presence of the same type of cancer(e.g., having the same tissue or origin) as the cancer that wasoriginally detected (e.g., based, at least in part, on the cfDNAfragmentation profile of the mammal). Additionally or alternatively, thediagnostic testing method can determine the presence of a different typeof cancer as the cancer that was original detected. In some cases, thediagnostic testing method is a scan. In some cases, the scan is acomputed tomography (CT), a CT angiography (CTA), a esophagram (a Bariumswallom), a Barium enema, a magnetic resonance imaging (MRI), a PETscan, an ultrasound (e.g., an endobronchial ultrasound, an endoscopicultrasound), an X-ray, a DEXA scan. In some cases, the diagnostictesting method is a physical examination, such as an anoscopy, abronchoscopy (e.g., an autofluorescence bronchoscopy, a white-lightbronchoscopy, a navigational bronchoscopy), a colonoscopy, a digitalbreast tomosynthesis, an endoscopic retrograde cholangiopancreatography(ERCP), an ensophagogastroduodenoscopy, a mammography, a Pap smear, apelvic exam, a positron emission tomography and computed tomography(PET-CT) scan. In some cases, a mammal that has been selected forfurther diagnostic testing can also be selected for increasedmonitoring. Once the presence of a tumor or a cancer (e.g., a cancercell) has been identified (e.g., by any of the variety of methodsdisclosed herein), it may be beneficial for the mammal to undergo bothincreased monitoring (e.g., to assess the progression of the tumor orcancer in the mammal and/or to assess the development of one or morecancer biomarkers such as mutations), and further diagnostic testing(e.g., to determine the size and/or exact location of the tumor or thecancer). In some cases, a cancer treatment is administered to the mammalthat is selected for further diagnostic testing after a cancer biomarkeris detected and/or after the cfDNA fragmentation profile of the mammalhas not improved or deteriorated. Any of the cancer treatments disclosedherein or known in the art can be administered. For example, a mammalthat has been selected for further diagnostic testing can beadministered a further diagnostic test, and a cancer treatment can beadministered if the presence of the tumor or the cancer is confirmed.Additionally or alternatively, a mammal that has been selected forfurther diagnostic testing can be administered a cancer treatment, andcan be further monitored as the cancer treatment progresses. In somecases, after a mammal that has been selected for further diagnostictesting has been administered a cancer treatment, the additional testingwill reveal one or more cancer biomarkers (e.g., mutations). In somecases, such one or more cancer biomarkers (e.g., mutations) will providecause to administer a different cancer treatment (e.g., a resistancemutation may arise in a cancer cell during the cancer treatment, whichcancer cell harboring the resistance mutation is resistant to theoriginal cancer treatment).

The invention will be further described in the following examples, whichdo not limit the scope of the invention described in the claims.

EXAMPLES Example 1: Cell-Free DIVA Fragmentation in Patients with Cancer

Analyses of cell free DNA have largely focused on targeted sequencing ofspecific genes. Such studies permit detection of a small number oftumor-specific alterations in patients with cancer and not all patients,especially those with early stage disease, have detectable changes.Whole genome sequencing of cell-free DNA can identify chromosomalabnormalities and rearrangements in cancer patients but detection ofsuch alterations has been challenging in part due to the difficulty indistinguishing a small number of abnormal from normal chromosomalchanges (Leary et al., 2010 Sci Transl Med 2:20ra14; and Leary et al.,2012 Sci Transl Med 4:162ra154). Other efforts have suggested nucleosomepatterns and chromatin structure may be different between cancer andnormal tissues, and that cfDNA in patients with cancer may result inabnormal cfDNA fragment size as well as position (Snyder et al., 2016Cell 164:57; Jahr et al., 2001 Cancer Res 61:1659; Ivanov et al., 2015BMC Genomics 16(Suppl 13):S1). However, the amount of sequencing neededfor nucleosome footprint analyses of cfDNA is impractical for routineanalyses.

The sensitivity of any cell-free DNA approach depends on the number ofpotential alterations examined as well as the technical and biologicallimitations of detecting such changes. As a typical blood samplecontains ˜2000 genome equivalents of cfDNA per milliliter of plasma(Phallen et al., 2017 Sci Transl Med 9), the theoretical limit ofdetection of a single alteration can be no better than one in a fewthousand mutant to wild-type molecules. An approach that detects alarger number of alterations in the same number of genome equivalentswould be more sensitive for detecting cancer in the circulation. MonteCarlo simulations show that increasing the number of potentialabnormalities detected from only a few to tens or hundreds canpotentially improve the limit of detection by orders of magnitude,similar to recent probability analyses of multiple methylation changesin cfDNA (FIG. 2).

This study presents a novel method called DELFI for detection of cancerand further identification of tissue of origin using whole genomesequencing (FIG. 1). The approach uses cfDNA fragmentation profiles andmachine learning to distinguish patterns of healthy blood cell DNA fromtumor-derived DNA and to identify the primary tumor tissue. DELFI wasused for a retrospective analysis of cfDNA from 245 healthy individualsand 236 patients with breast, colorectal, lung, ovarian, pancreatic,gastric, or bile duct cancers, with most patients exhibiting localizeddisease. Assuming this approach had sensitivity ≥0.80 for discriminatingcancer patients from healthy individuals while maintaining a specificityof 0.95, a study of at least 200 cancer patients would enable estimationof the true sensitivity with a margin of error of 0.06 at the desiredspecificity of 0.95 or greater.

Materials and Methods Patient and Sample Characteristics

Plasma samples from healthy individuals and plasma and tissue samplesfrom patients with breast, lung, ovarian, colorectal, bile duct, orgastric cancer were obtained from ILSBio/Bioreclamation, AarhusUniversity, Herlev Hospital of the University of Copenhagen, HvidovreHospital, the University Medical Center of the University of Utrecht,the Academic Medical Center of the University of Amsterdam, theNetherlands Cancer Institute, and the University of California, SanDiego. All samples were obtained under Institutional Review Boardapproved protocols with informed consent for research use atparticipating institutions. Plasma samples from healthy individuals wereobtained at the time of routine screening, including for colonoscopiesor Pap smears. Individuals were considered healthy if they had noprevious history of cancer and negative screening results.

Plasma samples from individuals with breast, colorectal, gastric, lung,ovarian, pancreatic, and bile duct cancer were obtained at the time ofdiagnosis, prior to tumor resection or therapy. Nineteen lung cancerpatients analyzed for change in cfDNA fragmentation profiles acrossmultiple time points were undergoing treatment with anti-EGFR oranti-ERBB2 therapy (see, e.g., Phallen et al., 2019 Cancer Research 15,1204-1213). Clinical data for all patients included in this study arelisted in Table 1 (Appendix A). Gender was confirmed through genomicanalyses of X and Y chromosome representation. Pathologic staging ofgastric cancer patients was performed after neoadjuvant therapy. Sampleswhere the tumor stage was unknown were indicated as stage X or unknown.

Nucleosomal DNA Purification

Viably frozen lymphocytes were elutriated from leukocytes obtained froma healthy male (C0618) and female (D0808-L) (Advanced BiotechnologiesInc., Eldersburg, Md.). Aliquots of 1×10⁶ cells were used fornucleosomal DNA purification using EZ Nucleosomal DNA Prep Kit (ZymoResearch, Irvine, Calif.). Cells were initially treated with 100 μl ofNuclei Prep Buffer and incubated on ice for 5 minutes. Aftercentrifugation at 200 g for 5 minutes, supernatant was discarded andpelleted nuclei were treated twice with 1000 of Atlantis DigestionBuffer or with 100 μl of micrococcal nuclease (MN) Digestion Buffer.Finally, cellular nucleic DNA was fragmented with 0.5 U of AtlantisdsDNase at 42° C. for 20 minutes or 1.5 U of MNase at 37° C. for 20minutes. Reactions were stopped using 5×MN Stop Buffer and DNA waspurified using Zymo-Spin™ IIC Columns. Concentration and quality ofeluted cellular nucleic DNA were analyzed using the Bioanalyzer 2100(Agilent Technologies, Santa Clara, Calif.).

Sample Preparation and Sequencing of cfDNA

Whole blood was collected in EDTA tubes and processed immediately orwithin one day after storage at 4° C., or was collected in Streck tubesand processed within two days of collection for three cancer patientswho were part of the monitoring analysis. Plasma and cellular componentswere separated by centrifugation at 800 g for 10 min at 4° C. Plasma wascentrifuged a second time at 18,000 g at room temperature to remove anyremaining cellular debris and stored at −80° C. until the time of DNAextraction. DNA was isolated from plasma using the Qiagen CirculatingNucleic Acids Kit (Qiagen GmbH) and eluted in LoBind tubes (EppendorfAG). Concentration and quality of cfDNA were assessed using theBioanalyzer 2100 (Agilent Technologies).

NGS cfDNA libraries were prepared for whole genome sequencing andtargeted sequencing using 5 to 250 ng of cfDNA as described elsewhere(see, e.g., Phallen et al, 2017 Sci Transl Med 9:eaan2415). Briefly,genomic libraries were prepared using the NEBNext DNA Library Prep Kitfor Illumina [New England Biolabs (NEB)] with four main modifications tothe manufacturer's guidelines: (i) The library purification steps usedthe on-bead AMPure XP approach to minimize sample loss during elutionand tube transfer steps (see, e.g., Fisher et al., 2011 Genome Biol12:R1); (ii) NEBNext End Repair, A-tailing, and adapter ligation enzymeand buffer volumes were adjusted as appropriate to accommodate theon-bead AMPure XP purification strategy; (iii) a pool of eight uniqueIllumina dual index adapters with 8-base pair (bp) barcodes was used inthe ligation reaction instead of the standard Illumina single or dualindex adapters with 6- or 8-bp barcodes, respectively; and (iv) cfDNAlibraries were amplified with Phusion Hot Start Polymerase.

Whole genome libraries were sequenced directly. For targeted libraries,capture was performed using Agilent SureSelect reagents and a custom setof hybridization probes targeting 58 genes (see, e.g., Phallen et al.,2017 Sci Transl Med 9:eaan2415) per the manufacturer's guidelines. Thecaptured library was amplified with Phusion Hot Start Polymerase (NEB).Concentration and quality of captured cfDNA libraries were assessed onthe Bioanalyzer 2100 using the DNA1000 Kit (Agilent Technologies).Targeted libraries were sequenced using 100-bp paired-end runs on theIllumina HiSeq 2000/2500 (Illumina).

Analyses of Targeted Sequencing Data from cfDNA

Analyses of targeted NGS data for cfDNA samples was performed asdescribed elsewhere (see, e.g., Phallen et al., 2017 Sci Transl Med9:eaan2415). Briefly, primary processing was completed using IlluminaCASAVA (Consensus Assessment of Sequence and Variation) software(version 1.8), including demultiplexing and masking of dual-indexadapter sequences. Sequence reads were aligned against the humanreference genome (version hg18 or hg19) using NovoAlign with additionalrealignment of select regions using the Needleman-Wunsch method (see,e.g., Jones et al., 2015 Sci Transl Med 7:283ra53). The positions of thesequence alterations have not been affected by the different genomebuilds. Candidate mutations, consisting of point mutations, smallinsertions, and deletions, were identified using VariantDx (see, e.g.,Jones et al., 2015 Sci Transl Med 7:283ra53) (Personal GenomeDiagnostics, Baltimore, Md.) across the targeted regions of interest.

To analyze the fragment lengths of cfDNA molecules, each read pair froma cfDNA molecule was required to have a Phred quality score ≥30. Allduplicate ctDNA fragments, defined as having the same start, end, andindex barcode were removed. For each mutation, only fragments for whichone or both of the read pairs contained the mutated (or wild-type) baseat the given position were included. This analysis was done using the Rpackages Rsamtools and GenomicAlignments.

For each genomic locus where a somatic mutation was identified, thelengths of fragments containing the mutant allele were compared to thelengths of fragments of the wild-type allele. If more than 100 mutantfragments were identified, Welch's two-sample t-test was used to comparethe mean fragment lengths. For loci with fewer than 100 mutantfragments, a bootstrap procedure was implemented. Specifically,replacement N fragments containing the wild-type allele, where N denotesthe number of fragments with the mutation, were sampled. For eachbootstrap replicate of wild type fragments their median length wascomputed. The p-value was estimated as the fraction of bootstrapreplicates with a median wild-type fragment length as or more extremethan the observed median mutant fragment length.

Analyses of Whole Genome Sequencing Data from cfDNA

Primary processing of whole genome NGS data for cfDNA samples wasperformed using Illumina CASAVA (Consensus Assessment of Sequence andVariation) software (version 1.8.2), including demultiplexing andmasking of dual-index adapter sequences. Sequence reads were alignedagainst the human reference genome (version hg19) using ELAND.

Read pairs with a MAPQ score below 30 for either read and PCR duplicateswere removed. hg19 autosomes were tiled into 26,236 adjacent,non-overlapping 100 kb bins. Regions of low mappability, indicated bythe 10% of bins with the lowest coverage, were removed (see, e.g.,Fortin et al., 2015 Genome Biol 16:180), as were reads falling in theDuke blacklisted regions (see, e.g.,hgdownload.cse.ucsc.edu/goldenpath/hg19/encodeDCC/wgEncodeMapability/).Using this approach, 361 Mb (13%) of the hg19 reference genome wasexcluded, including centromeric and telomeric regions. Short fragmentswere defined as having a length between 100 and 150 bp and longfragments were defined has having a length between 151 and 220 bp.

To account for biases in coverage attributable to GC content of thegenome, the locally weighted smoother loess with span ¾ was applied tothe scatterplot of average fragment GC versus coverage calculated foreach 100 kb bin. This loess regression was performed separately forshort and long fragments to account for possible differences in GCeffects on coverage in plasma by fragment length (see, e.g., Benjaminiet al., 2012 Nucleic Acids Res 40:e72). The predictions for short andlong coverage explained by GC from the loess model were subtracted,obtaining residuals for short and long that were uncorrelated with GC.The residuals were returned to the original scale by adding back thegenome-wide median short and long estimates of coverage. This procedurewas repeated for each sample to account for possible differences in GCeffects on coverage between samples. To further reduce the feature spaceand noise, the total GC-adjusted coverage in 5 Mb bins was calculated.

To compare the variability of fragment lengths from healthy subjects tofragments in patients with cancer, the standard deviation of the shortto long fragmentation profiles for each individual was calculated. Thestandard deviations in the two groups were compared by a Wilcoxon ranksum test.

Analyses of Chromosome Arm Copy Number Changes

To develop arm-level statistics for copy number changes, an approach foraneuploidy detection in plasma as described elsewhere (see, e.g., Learyet al., 2012 Sci Transl Med 4:162ra154) was adopted. This approachdivides the genome into non-overlapping 50 KB bins for whichGC-corrected log 2 read depth was obtained after correction by loesswith span ¾. This loess-based correction is comparable to the approachoutlined above, but is evaluated on a log 2 scale to increase robustnessto outliers in the smaller bins and does not stratify by fragmentlength. To obtain an arm-specific Z-score for copy number changes, themean GC-adjusted read depth for each arm (GR) was centered and scaled bythe average and standard deviation, respectively, of GR scores obtainedfrom an independent set of 50 healthy samples.

Analyses of Mitochondrial-Aligned Reads from cfDNA

Whole genome sequence reads that initially mapped to the mitochondrialgenome were extracted from bam files and realigned to the hg19 referencegenome in end-to-end mode with Bowtie2 as described elsewhere (see,e.g., Langmead et al., 2012 Nat Methods 9:357-359). The resultingaligned reads were filtered such that both mates aligned to themitochondrial genome with MAPQ >=30. The number of fragments mapping tothe mitochondrial genome was counted and converted to a percentage ofthe total number of fragments in the original bam files.

Prediction Model for Cancer Classification

To distinguish healthy from cancer patients using fragmentationprofiles, a stochastic gradient boosting model was used (gbm; see, e.g.,Friedman et al., 2001 Ann Stat 29:1189-1232; and Friedman et al., 2002Comput Stat Data An 38:367-378). GC-corrected total and short fragmentcoverage for all 504 bins were centered and scaled for each sample tohave mean 0 and unit standard deviation. Additional features includedZ-scores for each of the 39 autosomal arms and mitochondrialrepresentation (log 10-transformed proportion of reads mapped to themitochondria). To estimate the prediction error of this approach,10-fold cross-validation was used as described elsewhere (see, e.g.,Efron et al., 1997 J Am Stat Assoc 92, 548-560). Feature selection,performed only on the training data in each cross-validation run,removed bins that were highly correlated (correlation >0.9) or had nearzero variance. Stochastic gradient boosted machine learning wasimplemented using the R package gbm package with parameters n.trees=150,interaction.depth=3, shrinkage=0.1, and n.minobsinside=10. To averageover the prediction error from the randomization of patients to folds,the 10-fold cross validation procedure was repeated 10 times. Confidenceintervals for sensitivity fixed at 98% and 95% specificity were obtainedfrom 2000 bootstrap replicates.

Prediction Model for Tumor Tissue of Origin Classification

For samples correctly classified as cancer patients at 90% specificity(n=174), a separate stochastic gradient boosting model was trained toclassify the tissue of origin. To account for the small number of lungsamples used for prediction, 18 cfDNA baseline samples from late stagelung cancer patients were included from the monitoring analyses.Performance characteristics of the model were evaluated by 10-foldcross-validation repeated 10 times. This gbm model was trained using thesame features as in the cancer classification model. As previouslydescribed, features that displayed correlation above 0.9 to each otheror had near zero variance were removed within each training datasetduring cross-validation. The tissue class probabilities were averagedacross the 10 replicates for each patient and the class with the highestprobability was taken as the predicted tissue.

Analyses of Nucleosomal DNA from Human Lymphocytes and cfDNA

From the nuclease treated lymphocytes, fragment sizes were analyzed in 5Mb bins as described for whole genome cfDNA analyses. A genome-wide mapof nucleosome positions was constructed from the nuclease treatedlymphocyte cell-lines. This approach identified local biases in thecoverage of circulating fragments, indicating a region protected fromdegradation. A “Window positioning score” (WPS) was used to score eachbase pair in the genome (see, e.g., Snyder et al., 2016 Cell 164:57).Using a sliding window of 60 bp centered around each base, the WPS wascalculated as the number of fragments completely spanning the windowminus the number of fragments with only one end in the window. Sincefragments arising from nucleosomes have a median length of 167 bp, ahigh WPS indicated a possible nucleosomic position. WPS scores werecentered at zero using a running median and smoothed using aKolmogorov-Zurbenko filter (see, e.g., Zurbenko, The spectral analysisof time series. North-Holland series in statistics and probability;Elsevier, New York, N Y, 1986). For spans of positive WPS between 50 and450 bp, a nucleosome peak was defined as the set of base pairs with aWPS above the median in that window. The calculation of nucleosomepositions for cfDNA from 30 healthy individuals with sequence coverageof 9× was determined in the same manner as for lymphocyte DNA. To ensurethat nucleosomes in healthy cfDNA were representative, a consensus trackof nucleosomes was defined consisting only of nucleosomes identified intwo or more individuals. Median distances between adjacent nucleosomeswere calculated from the consensus track.

Monte Carlo Simulation of Detection Sensitivity

A Monte Carlo simulation was used to estimate the probability ofdetecting a molecule with a tumor-derived alteration. Briefly, 1 millionmolecules were generated from a multinomial distribution. For asimulation with m alterations, wild-type molecules were simulated withprobability p and each of the m tumor alterations were simulated withprobability (1−p)/m. Next, g*m molecules were sampled randomly withreplacement, where g denotes the number of genome equivalents in 1 ml ofplasma. If a tumor alteration was sampled s or more times, the samplewas classified as cancer-derived. The simulation was repeated 1000times, estimating the probability that the in silico sample would becorrectly classified as cancer by the mean of the cancer indicator.Setting g=2000 and s=5, the number of tumor alterations was varied bypowers of 2 from 1 to 256 and the fraction of tumor-derived moleculesfrom 0.0001% to 1%.

Statistical Analyses

All statistical analyses were performed using R version 3.4.3. The Rpackages caret (version 6.0-79) and gbm (version 2.1-4) were used toimplement the classification of healthy versus cancer and tissue oforigin. Confidence intervals from the model output were obtained withthe pROC (version 1.13) R package (see, e.g., Robin et al., 2011 BMCbioinformatics 12:77). Assuming the prevalence of undiagnosed cancercases in this population is high (1 or 2 cases per 100 healthy), agenomic assay with a specificity of 0.95 and sensitivity of 0.8 wouldhave useful operating characteristics (positive predictive value of 0.25and negative predictive value near 1). Power calculations suggest thatan analysis of more than 200 cancer patients and an approximately equalnumber of healthy controls, enable an estimation of the sensitivity witha margin of error of 0.06 at the desired specificity of 0.95 or greater.

Data and Code Availability

Sequence data utilized in this study have been deposited at the EuropeanGenome-phenome Archive under study accession nos. EGAS00001003611 andEGAS00001002577. Code for analyses is available atgithub.com/Cancer-Genomics/delfi_scripts.

Results

DELFI allows simultaneous analysis of a large number of abnormalities incfDNA through genome-wide analysis of fragmentation patterns. The methodis based on low coverage whole genome sequencing and analysis ofisolated cfDNA. Mapped sequences are analyzed in non-overlapping windowscovering the genome. Conceptually, windows may range in size fromthousands to millions of bases, resulting in hundreds to thousands ofwindows in the genome. 5 Mb windows were used for evaluating cfDNAfragmentation patterns as these would provide over 20,000 reads perwindow even at a limited amount of 1-2× genome coverage. Within eachwindow, the coverage and size distribution of cfDNA fragments wasexamined. This approach was used to evaluate the variation ofgenome-wide fragmentation profiles in healthy and cancer populations(Table 1; Appendix A). The genome-wide pattern from an individual can becompared to reference populations to determine if the pattern is likelyhealthy or cancer-derived. As genome-wide profiles reveal positionaldifferences associated with specific tissues that may be missed inoverall fragment size distributions, these patterns may also indicatethe tissue source of cfDNA.

The fragmentation size of cfDNA was focused on as it was found thatcancer-derived cfDNA molecules may be more variable in size than cfDNAderived from non-cancer cells. cfDNA fragments from targeted regionsthat were captured and sequenced at high coverage (43,706 totalcoverage, 8,044 distinct coverage) from patients with breast,colorectal, lung or ovarian cancer (Table 1 (Appendix A), Table 2(Appendix B), and Table 3 (Appendix C)) were initially examined.Analyses of loci containing 165 tumor-specific alterations from 81patients (range of 1-7 alterations per patient) revealed an averageabsolute difference of 6.5 bp (95% CI, 5.4-7.6 bp) between lengths ofmedian mutant and wild-type cfDNA fragments (FIG. 3, Table 3 (AppendixC)). The median size of mutant cfDNA fragments ranged from 30 basessmaller at chromosome 3 position 41,266,124 to 47 bases larger atchromosome 11 position 108,117,753 than the wild-type sequences at theseregions (Table 3; Appendix C). GC content was similar for mutated andnon-mutated fragments (FIG. 4a ), and there was no correlation betweenGC content and fragment length (FIG. 4b ). Similar analyses of 44germline alterations from 38 patients identified median cfDNA sizedifferences of less than 1 bp between fragment lengths of differentalleles (FIG. 5, Table 3 (Appendix C)). Additionally, 41 alterationsrelated to clonal hematopoiesis were identified through a previoussequence comparison of DNA from plasma, buffy coat, and tumors of thesame individuals. Unlike tumor-derived fragments, there were nosignificant differences between fragments with hematopoietic alterationsand wild type fragments (FIG. 6, Table 3 (Appendix C)). Overall,cancer-derived cfDNA fragment lengths were significantly more variablecompared to non-cancer cfDNA fragments at certain genomic regions(p<0.001, variance ratio test). It was hypothesized that thesedifferences may be due to changes in higher-order chromatin structure aswell as other genomic and epigenomic abnormalities in cancer and thatcfDNA fragmentation in a position-specific manner could therefore serveas a unique biomarker for cancer detection.

As targeted sequencing only analyzes a limited number of loci,larger-scale genome-wide analyses to detect additional abnormalities incfDNA fragmentation were investigated. cfDNA was isolated from ˜4 ml ofplasma from 8 lung cancer patients with stage I-III disease, as well asfrom 30 healthy individuals (Table 1 (Appendix A), Table 4 (Appendix D),and Table 5 (Appendix E)). A high efficiency approach was used toconvert cfDNA to next generation sequencing libraries and performedwhole genome sequencing at ˜9× coverage (Table 4; Appendix D). OverallcfDNA fragment lengths of healthy individuals were larger, with a medianfragment size of 167.3 bp, while patients with cancer had medianfragment sizes of 163.8 (p<0.01, Welch's t-test) (Table 5; Appendix E).To examine differences in fragment size and coverage in a positiondependent manner across the genome, sequenced fragments were mapped totheir genomic origin and fragment lengths were evaluated in 504 windowsthat were 5 Mb in size, covering ˜2.6 Gb of the genome. For each window,the fraction of small cfDNA fragments (100 to 150 bp in length) tolarger cfDNA fragments (151 to 220 bp) as well as overall coverage weredetermined and used to obtain genome-wide fragmentation profiles foreach sample.

Healthy individuals had very similar fragmentation profiles throughoutthe genome (FIG. 7 and FIG. 8). To examine the origins of fragmentationpatterns normally observed in cfDNA, nuclei were isolated fromelutriated lymphocytes of two healthy individuals and treated with DNAnucleases to obtain nucleosomal DNA fragments. Analyses of cfDNApatterns in observed healthy individuals revealed a high correlation tolymphocyte nucleosomal DNA fragmentation profiles (FIGS. 7b and 7d ) andnucleosome distances (FIGS. 7c and 7f ). Median distances betweennucleosomes in lymphocytes were correlated to open (A) and closed (B)compartments of lymphoblastoid cells as revealed using the Hi-C method(see, e.g., Lieberman-Aiden et al., 2009 Science 326:289-293; and Fortinet al., 2015 Genome Biol 16:180) for examining the three-dimensionalarchitecture of genomes (FIG. 7c ). These analyses suggest that thefragmentation patterns of normal cfDNA are the result of nucleosomal DNApatterns that largely reflect the chromatin structure of normal bloodcells.

In contrast to healthy cfDNA, patients with cancer had multiple distinctgenomic differences with increases and decreases in fragment sizes atdifferent regions (FIGS. 7a and 7b ). Similar to our observations fromtargeted analyses, there was also greater variation in fragment lengthsgenome-wide for patients with cancer compared to healthy individuals.

To determine whether cfDNA fragment length patterns could be used todistinguish patients with cancer from healthy individuals, genome-widecorrelation analyses were performed of the fraction of short to longcfDNA fragments for each sample compared to the median fragment lengthprofile calculated from healthy individuals (FIGS. 7a, 7b, and 7e ).While the profiles of cfDNA fragments were remarkably consistent amonghealthy individuals (median correlation of 0.99), the median correlationof genome-wide fragment ratios among cancer patients was 0.84 (0.15lower, 95% CI 0.07-0.50, p<0.001, Wilcoxon rank sum test; Table 5(Appendix E)). Similar differences were observed when comparingfragmentation profiles of cancer patients to fragmentation profiles ornucleosome distances in healthy lymphocytes (FIGS. 7c, 7d, and 7f ). Toaccount for potential biases in the fragmentation profiles attributableto GC content, a locally weighted smoother was applied independently toeach sample and found that differences in fragmentation profiles betweenhealthy individuals and cancer patients remained after this adjustment(median correlation of cancer patients to healthy=0.83) (Table 5;Appendix E).

Subsampling analyses of whole genome sequence data was performed at 9×coverage from cfDNA of patients with cancer at ˜2×, ˜1×, ˜0.5×, ˜0.2×,and ˜0.1× genome coverage, and it was determined that alteredfragmentation profiles were readily identified even at 0.5× genomecoverage (FIG. 9). Based on these observations, whole genome sequencingwas performed with coverage of 1-2× to evaluate whether fragmentationprofiles may change during the course of targeted therapy in a mannersimilar to monitoring of sequence alterations. cfDNA from 19 non-smallcell lung cancer patients including 5 with partial radiographicresponse, 8 with stable disease, 4 with progressive disease, and 2 withunmeasurable disease, during the course of anti-EGFR or anti-ERBB2therapy was evaluated (Table 6; Appendix F). As shown in FIG. 10, thedegree of abnormality in the fragmentation profiles during therapyclosely matched levels of EGFR or ERBB2 mutant allele fractions asdetermined using targeted sequencing (Spearman correlation of mutantallele fractions to fragmentation profiles=0.74). This correlation isremarkable as genome-wide and mutation-based methods are orthogonal andexamine different cfDNA alterations that may be suppressed in thesepatients due to prior therapy. Notably all cases that had progressionfree survival of six or more months displayed a drop of or had extremelylow levels of ctDNA after initiation of therapy as determined byfragmentation profiles, while cases with poor clinical outcome hadincreases in ctDNA. These results demonstrate the feasibility offragmentation analyses for detecting the presence of tumor-derivedcfDNA, and suggests that such analyses may also be useful forquantitative monitoring of cancer patients during treatment.

The fragmentation profiles were examined in the context of known copynumber changes in a patient where parallel analyses of tumor tissue wereobtained. These analyses demonstrated that altered fragmentationprofiles were present in regions of the genome that were copy neutraland that these may be further affected in regions with copy numberchanges (FIG. 11a and FIG. 12a ). Position dependent differences infragmentation patterns could be used to distinguish cancer-derived cfDNAfrom healthy cfDNA in these regions (FIG. 12a, b ), while overall cfDNAfragment size measurements would have missed such differences (FIG. 12a).

These analyses were extended to an independent cohort of cancer patientsand healthy individuals. Whole genome sequencing of cfDNA at 1-2×coverage from a total of 208 patients with cancer, including breast(n=54), colorectal (n=27), lung (n=12), ovarian (n=28), pancreatic(n=34), gastric (n=27), or bile duct cancers (n=26), as well as 215individuals without cancer was performed (Table 1 (Appendix A) and Table4 (Appendix D)). All cancer patients were treatment naïve and themajority had resectable disease (n=183). After GC adjustment of shortand long cfDNA fragment coverage (FIG. 13a ), coverage and sizecharacteristics of fragments in windows throughout the genome wereexamined (FIG. 11b , Table 4 (Appendix D) and Table 7 (Appendix G)).Genome-wide correlations of coverage to GC content were limited and nodifferences in these correlations between cancer patients and healthyindividuals were observed (FIG. 13b ). Healthy individuals had highlyconcordant fragmentation profiles, while patients with cancer had highvariability with decreased correlation to the median healthy profile(Table 7; Appendix G). An analysis of the most commonly alteredfragmentation windows in the genome among cancer patients revealed amedian of 60 affected windows across the cancer types analyzed,highlighting the multitude of position dependent alterations infragmentation of cfDNA in individuals with cancer (FIG. 11c ).

To determine if position dependent fragmentation changes can be used todetect individuals with cancer, a gradient tree boosting machinelearning model was implemented to examine whether cfDNA can becategorized as having characteristics of a cancer patient or healthyindividual and estimated performance characteristics of this approach byten-fold cross validation repeated ten times (FIGS. 14 and 15). Themachine learning model included GC-adjusted short and long fragmentcoverage characteristics in windows throughout the genome. A machinelearning classifier for copy number changes from chromosomal armdependent features rather than a single score was also developed (FIG.16a and Table 8 (Appendix H)) and mitochondrial copy number changes werealso included (FIG. 16b ) as these could also help distinguish cancerfrom healthy individuals. Using this implementation of DELFI, a scorewas obtained that could be used to classify patients as healthy orhaving cancer. 152 of the 208 cancer patients were detected (73%sensitivity, 95% CI 67%-79%) while four of the 215 healthy individualswere misclassified (98% specificity) (Table 9). At a threshold of 95%specificity, 80% of patients with cancer were detected (95% CI,74%-85%), including 79% of resectable (stage I-III) patients (145 of183) and 82% of metastatic (stage IV) patients (18 out of 22) (Table 9).Receiver operator characteristic analyses for detection of patients withcancer had an AUC of 0.94 (95% CI 0.92-0.96), ranged among cancer typesfrom 0.86 for pancreatic cancer to ≥0.99 for lung and ovarian cancers(FIGS. 17a and 17b ), and had AUCs ≥0.92 across all stages (FIG. 18).The DELFI classifier score did not differ with age among either cancerpatients or healthy individuals (Table 1; Appendix A).

TABLE 9 DELFI performance for cancer detection. 95% specificity 98%specificity Individuals Individuals Individuals analyzed detectedSensitivity 95% Cl detected Sensitivity 95% Cl Healthy 215 10 — — 4 — —Cancer 208 166  80% 74%-85% 152  73% 67%-79% Type Breast 54 38  70%56%-82% 31  57% 43%-71% Bile duct 26 23  88% 70%-98% 21  81% 61%-93%Colorectal 27 22  81% 62%-94% 19  70% 50%-86% Gastric 27 22  81% 62%-94%22  81% 62%-94% Lung 12 12 100%  74%-100% 12 100%  74%-100% Ovarian 2825  89% 72%-98% 25  89% 72%-98% Pancreatic 34 24  71% 53%-85% 22  65%46%-80% Stage I 41 30  73% 53%-86% 28  68% 52%-82% II 109 85  78%69%-85% 78  72% 62%-80% III 33 30  91% 76%-98% 26  79% 61%-91% IV 22 18 82% 60%-95% 17  77% 55%-92% 0, X 3 3 100%  29%-100% 3 100%  29%-100%

To assess the contribution of fragment size and coverage, chromosome armcopy number, or mitochondrial mapping to the predictive accuracy of themodel, the repeated 10-fold cross-validation procedure was implementedto assess performance characteristics of these features in isolation. Itwas observed that fragment coverage features alone (AUC=0.94) werenearly identical to the classifier that combined all features (AUC=0.94)(FIG. 17a ). In contrast, analyses of chromosomal copy number changeshad lower performance (AUC=0.88) but were still more predictive thancopy number changes based on individual scores (AUC=0.78) ormitochondrial mapping (AUC=0.72) (FIG. 17a ). These results suggest thatfragment coverage is the major contributor to our classifier. Includingall features in the prediction model may contribute in a complementaryfashion for detection of patients with cancer as they can be obtainedfrom the same genome sequence data.

As fragmentation profiles reveal regional differences in fragmentationthat may differ between tissues, a similar machine learning approach wasused to examine whether cfDNA patterns could identify the tissue oforigin of these tumors. It was found that this approach had a 61%accuracy (95% CI 53%-67%), including 76% for breast, 44% for bile duct,71% for colorectal, 67% for gastric, 53% for lung, 48% for ovarian, and50% for pancreatic cancers (FIG. 19, Table 10). The accuracy increasedto 75% (95% CI 69%-81%) when considering assigning patients withabnormal cfDNA to one of two sites of origin (Table 10). For all tumortypes, the classification of the tissue of origin by DELFI wassignificantly higher than determined by random assignment (p<0.01,binomial test, Table 10).

TABLE 10 DELFI tissue of origin prediction Cancer Patients TopPrediction Top Two Predictions Random Assignment Type Detected* PatientsAccuracy (95% Cl) Patients Accuracy (95% Cl) Patients Accuracy Breast 4232 76% (61%-88%) 38 91% (77%-97%) 9 22% Bile Duct 23 10 44% (23%-66%) 1565% (43%-84%) 3 12% Colorectal 24 17 71% (49%-87%) 19 79% (58%-93%) 312% Gastric 24 16 67% (45%-84%) 19 79% (58%-93%) 3 12% Lung 30 16 53%(34%-72%) 23 77% (58%-90%) 2  6% Ovarian 27 13 48% (29%-68%) 16 59%(38%-78%) 4 14% Pancreatic 24 12 50% (29%-71%) 16 67% (45%-84%) 3 12%Total 194 116 61% (53%-67%) 146 75% (69%-81%) 26 13% *Patients detectedare based on DELFI detection at 90% specificity. Lung cohort includesadditional lung cancer patients with prior therapy.

As cancer-specific sequence alterations can be used to identify patientswith cancer, it was evaluated whether combining DELFI with this approachcould increase the sensitivity of cancer detection (FIG. 20). Ananalysis of cfDNA from a subset of the treatment naïve cancer patientsusing both DELFI and targeted sequencing revealed that 82% (103 of 126)of patients had fragmentation profile alterations, while 66% (83 of 126)had sequence alterations. Over 89% of cases with mutant allelefractions >1% were detected by DELFI while for cases with mutant allelefractions <1% the fraction detected by DELFI was 80%, including forcases that were undetectable using targeted sequencing (Table 7;Appendix G). When these approaches were used together, the combinedsensitivity of detection increased to 91% (115 of 126 patients) with aspecificity of 98% (FIG. 20).

Overall, genome-wide cfDNA fragmentation profiles are different betweencancer patients and healthy individuals. The variability in fragmentlengths and coverage in a position dependent manner throughout thegenome may explain the apparently contradictory observations of previousanalyses of cfDNA at specific loci or of overall fragment sizes. Inpatients with cancer, heterogeneous fragmentation patterns in cfDNAappear to be a result of mixtures of nucleosomal DNA from both blood andneoplastic cells. These studies provide a method for simultaneousanalysis of tens to potentially hundreds of tumor-specific abnormalitiesfrom minute amounts of cfDNA, overcoming a limitation that has precludedthe possibility of more sensitive analyses of cfDNA. DELFI analysesdetected a higher fraction of cancer patients than previous cfDNAanalysis methods that have focused on sequence or overall fragmentationsizes (see, e.g., Phallen et al., 2017 Sci Transl Med 9:eaan2415; Cohenet al., 2018 Science 359:926; Newman et al., 2014 Nat Med 20:548;Bettegowda et al., 2014 Sci Transl Med 6:224ra24; Newman et al., 2016Nat Biotechnol 34:547). As demonstrated in this Example, combining DELFIwith analyses of other cfDNA alterations may further increase thesensitivity of detection. As fragmentation profiles appear related tonucleosomal DNA patterns, DELFI may be used for determining the primarysource of tumor-derived cfDNA. The identification of the source ofcirculating tumor DNA in over half of patients analyzed may be furtherimproved by including clinical characteristics, other biomarkers,including methylation changes, and additional diagnostic approaches(Ruibal Morell, 1992 The International journal of biological markers7:160; Galli et al., 2013 Clinical chemistry and laboratory medicine51:1369; Sikaris, 2011 Heart, lung &circulation 20:634; Cohen et al.,2018 Science 359:926). Finally, this approach requires only a smallamount of whole genome sequencing, without the need for deep sequencingtypical of approaches that focus on specific alterations. Theperformance characteristics and limited amount of sequencing needed forDELFI suggests that our approach could be broadly applied for screeningand management of patients with cancer.

These results demonstrate that genome-wide cfDNA fragmentation profilesare different between cancer patients and healthy individuals. As such,cfDNA fragmentation profiles can have important implications for futureresearch and applications of non-invasive approaches for detection ofhuman cancer.

OTHER EMBODIMENTS

It is to be understood that while the invention has been described inconjunction with the detailed description thereof, the foregoingdescription is intended to illustrate and not limit the scope of theinvention, which is defined by the scope of the appended claims. Otheraspects, advantages, and modifications are within the scope of thefollowing claims.

APPENDIX A Table 1. Summary or patients and samples analyzed Whole AgeDegree Location of Volume cfDNA Genome Targeted at Site of Histopa- ofMetastases of Ex- cfDNA Fragment Fragment Targeted Patient Sample Diag-TNM Primary thological Differ- at Plasma tracted Input Profile ProfileMutation Patient Type Type Timepoint nosis Gender Stage Staging TumorDiagnosis entiation Diagnosis (ml) (ng/ml) (ng/ml) Analysis AnalysisAnalysis CGCRC291 Colorectal cfDNA Preoperative 69 F IV T3N2M1 CoecumAdencarcinoma Moderate Synchronous 7.9 7.80 7.80 Y Y Y Cancer treatmentnaive Liver CGCRC292 Colorectal cfDNA Preoperative 51 M IV T3N2M1 SigmodAdencarcinoma Moderate Synchronous 7.9 6.73 6.73 Y Y Y Cancer treatmentnaive Colon Liver, Lung CGCRC293 Colorectal cfDNA Preoperative 55 M IVT3N2M1 Rectum Adencarcinoma Moderate Synchronous 7.2 3.83 3.83 Y Y YCancer treatment naive Liver CGCRC294 Colorectal cfDNA Preoperative 67 FII T3N0M0 Sigmod Adencarcinoma Moderate None 8.4 18.87 18.87 Y Y YCancer treatment naive Colon CGCRC296 Colorectal cfDNA Preoperative 76 FII T4N0M0 Coecum Adencarcinoma Poor None 4.3 31.24 31.24 Y Y Y Cancertreatment naive CGCRC299 Colorectal cfDNA Preoperative 71 M I T1N0M0Rectum Adencarcinoma Moderate None 8.8 10.18 10.18 Y Y Y Cancertreatment naive CGCRC300 Colorectal cfDNA Preoperative 65 M I T2N0M0Rectum Adencarcinoma Moderate None 4.3 10.48 10.48 Y Y Y Cancertreatment naive CGCRC301 Colorectal cfDNA Preoperative 76 F I T2N0M0Rectum Adencarcinoma Moderate None 4.1 6.51 6.51 Y Y Y Cancer treatmentnaive CGCRC302 Colorectal cfDNA Preoperative 73 M II T3N0M0 TraverseAdencarcinoma Moderate None 4.3 52.13 52.13 Y Y Y Cancer treatment naiveColon CGCRC304 Colorectal cfDNA Preoperative 86 F II T3N0M0 RectumAdencarcinoma Moderate None 4.1 30.19 30.19 Y Y Y Cancer treatment naiveCGCRC305 Colorectal cfDNA Preoperative 83 F II T3N0M0 TraverseAdencarcinoma Moderate None 8.6 9.10 9.10 Y Y Y Cancer treatment naiveColon CGCRC306 Colorectal cfDNA Preoperative 80 F II T4N0M0 AscendingAdencarcinoma Moderate None 4.5 24.31 24.31 Y Y Y Cancer treatment naiveColon CGCRC307 Colorectal cfDNA Preoperative 78 F II T3N0M0 AscendingAdencarcinoma Moderate None 8.5 14.26 14.26 Y Y Y Cancer treatment naiveColon CGCRC308 Colorectal cfDNA Preoperative 72 F III T4N2M0 AscendingAdencarcinoma Moderate None 4.3 46.37 46.37 Y Y Y Cancer treatment naiveColon CGCRC311 Colorectal cfDNA Preoperative 59 M I T2N0M0 SigmodAdencarcinoma Moderate None 8.5 3.91 3.91 Y Y Y Cancer treatment naiveColon CGCRC315 Colorectal cfDNA Preoperative 74 M III T3N1M0 SigmodAdencarcinoma Moderate None 8.6 9.67 9.67 Y Y Y Cancer treatment naiveColon CGCRC316 Colorectal cfDNA Preoperative 80 M III T3N2M0 TraverseAdencarcinoma Moderate None 4.9 52.16 52.16 Y Y Y Cancer treatment naiveColon CGCRC317 Colorectal cfDNA Preoperative 74 M III T3N2M0 DescendingAdencarcinoma Moderate None 8.8 16.08 16.08 Y Y Y Cancer treatment naiveColon CGCRC318 Colorectal cfDNA Preoperative 81 M I T2N0M0 CoecumAdencarcinoma Moderate None 9.8 18.24 18.24 Y Y Y Cancer treatment naiveCGCRC319 Colorectal cfDNA Preoperative 80 F III T2N1M0 DescendingAdencarcinoma Moderate None 4.2 53.84 53.84 Y N Y Cancer treatment naiveColon CGCRC320 Colorectal cfDNA Preoperative 73 F I T2N0M0 AscendingAdencarcinoma Moderate None 4.5 30.37 30.37 Y Y Y Cancer treatment naiveColon CGCRC321 Colorectal cfDNA Preoperative 68 M I T2N0M0 RectumAdencarcinoma Moderate None 9.3 4.25 4.25 Y Y Y Cancer treatment naiveCGCRC333 Colorectal cfDNA Preoperative NA F IV NA Colon/ AdencarcinomaNA Liver 4.0 113.88 113.88 Y Y Y Cancer treatment naive Rectum CGCRC336Colorectal cfDNA Preoperative NA M IV NA Colon/ Adencarcinoma NA Liver4.4 211.74 211.74 Y Y Y Cancer treatment naive Rectum CGCRC338Colorectal cfDNA Preoperative NA F IV NA Colon/ Adencarcinoma NA Liver2.3 109.76 109.76 Y Y Y Cancer treatment naive Rectum CGCRC341Colorectal cfDNA Preoperative NA F IV NA Colon/ Adencarcinoma NA Liver4.6 156.62 156.62 Y N Y Cancer treatment naive Rectum CGCRC342Colorectal cfDNA Preoperative NA M IV NA Colon/ Adencarcinoma NA Liver3.9 56.09 56.09 Y N Y Cancer treatment naive Rectum CGLU316 Lung cfDNAPre-treatment, 50 F IV T3N2M0 Left Upper Adeno, Poor Lung 5.0 2.38 2.38Y N Y Cancer Day 53 Lobe of Lung Squamous, Small Cell Carcinoma CGLU316Lung cfDNA Pre-treatment, 50 F IV T3N2M0 Left Upper Adeno, Poor Lung 5.02.11 2.11 Y N Y Cancer Day −4 Lobe of Lung Squamous, Small CellCarcinoma CGLU316 Lung cfDNA Post-treatment, 50 F IV T3N2M0 Left UpperAdeno, Poor Lung 5.0 0.87 1.07 Y N Y Cancer Day 18 Lobe of LungSquamous, Small Cell Carcinoma CGLU316 Lung cfDNA Post-treatment, 50 FIV T3N2M0 Left Upper Adeno, Poor Lung 2.0 8.74 8.75 Y N Y Cancer Day 87Lobe of Lung Squamous, Small Cell Carcinoma CGLU344 Lung cfDNAPre-treatment, 65 F IV T2N2M1 Right Upper Adencarcinoma NA Pleura, 5.034.77 25.00 Y N Y Cancer Day −21 Lobe of Lung Liver, Pentoneum CGLU344Lung cfDNA Pre-treatment, 65 F IV T2N2M1 Right Upper Adencarcinoma NAPleura, 5.0 15.63 15.64 Y N Y Cancer Day 0 Lobe of Lung Liver, PentoneumCGLU344 Lung cfDNA Post-treatment, 65 F IV T2N2M1 Right UpperAdencarcinoma NA Pleura, 5.0 9.22 9.22 Y N Y Cancer Day 0.1875 Lobe ofLung Liver, Pentoneum CGLU344 Lung cfDNA Post-treatment, 65 F IV T2N2M1Right Upper Adencarcinoma NA Pleura, 5.0 5.31 5.32 Y N Y Cancer Day 59Lobe of Lung Liver, Pentoneum CGLU369 Lung cfDNA Pre-treatment, 48 F IVT2NxM1 Right Upper Adencarcinoma NA Brain 2.0 11.28 11.28 Y N Y CancerDay −2 Lobe of Lung CGLU369 Lung cfDNA Post-treatment, 48 F IV T2NxM1Right Upper Adencarcinoma NA Brain 5.0 10.09 10.09 Y N Y Cancer Day 12Lobe of Lung CGLU369 Lung cfDNA Post-treatment, 48 F IV T2NxM1 RightUpper Adencarcinoma NA Brain 5.0 6.69 6.70 Y N Y Cancer Day 88 Lobe ofLung CGLU369 Lung cfDNA Post-treatment, 48 F IV T2NxM1 Right UpperAdencarcinoma NA Brain 5.0 8.41 8.42 Y N Y Cancer Day 110 Lobe of LungCGLU373 Lung cfDNA Pre-treatment, 56 F IV T3N1M0 Right UpperAdencarcinoma Moderate None 5.0 6.35 6.35 Y N Y Cancer Day −2 Lobe ofLung CGLU373 Lung cfDNA Post-treatment, 56 F IV T3N1M0 Right UpperAdencarcinoma Moderate None 5.0 6.28 6.28 Y N Y Cancer Day 0.125 Lobe ofLung CGLU373 Lung cfDNA Post-treatment, 56 F IV T3N1M0 Right UpperAdencarcinoma Moderate None 5.0 3.82 3.82 Y N Y Cancer Day 7 Lobe ofLung CGLU373 Lung cfDNA Post-treatment, 56 F IV T3N1M0 Right UpperAdencarcinoma Moderate None 3.5 5.55 5.55 Y N Y Cancer Day 47 Lobe ofLung CGPLBR100 Breast cfDNA Preoperative 44 F III T2N2M0 Left BreastInfiltrating NA None 4.0 4.25 4.25 Y N Y Cancer treatment naive DuctalCarcinoma CGPLBR101 Breast cfDNA Preoperative 46 F II T2N1M0 Left BreastInfiltrating Moderate None 4.0 37.88 37.88 Y N Y Cancer treatment naiveLobular Carcinoma CGPLBR102 Breast cfDNA Preoperative 47 F II T2N1M0Right Breast Infiltrating Moderate None 3.6 13.67 13.67 Y N Y Cancertreatment naive Ductal Carcinoma CGPLBR103 Breast cfDNA Preoperative 48F II T2N1M0 Left Breast Infiltrating Moderate None 3.6 7.11 7.11 Y N YCancer treatment naive Ductal Carcinoma CGPLBR104 Breast cfDNAPreoperative 68 F II T2N0M0 Right Breast Infiltrating Moderate None 4.719.89 19.89 Y N Y Cancer treatment naive Lobular Carcinoma CGPLBR12Breast cfDNA Preoperative NA F III NA Breast Ductal NA NA 4.3 4.21 4.21Y N N Cancer treatment naive Carcinoma insitu with MicroinvasionCGPLBR18 Breast cfDNA Preoperative NA F III NA Breast Infiltrating NA NA4.1 40.39 30.49 Y N N Cancer treatment naive Lobular Carcinoma CGPLBR23Breast cfDNA Preoperative 53 F II NA Breast Infiltrating NA None 4.720.09 20.09 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR24Breast cfDNA Preoperative 53 F II NA Breast Infiltrating NA None 3.658.33 34.72 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR28Breast cfDNA Preoperative 59 F III NA Breast Infiltrating NA None 4.212.86 12.86 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR30Breast cfDNA Preoperative 61 F II NA Breast Infiltrating NA None 4.159.73 30.49 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR31Breast cfDNA Preoperative 54 F II NA Breast Infiltrating NA None 3.423.94 23.94 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR32Breast cfDNA Preoperative NA F II NA Breast Infiltrating NA None 4.471.23 28.41 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR33Breast cfDNA Preoperative 47 F II NA Breast Infiltrating NA None 4.411.00 11.00 Y N N Cancer treatment naive Lobular Carcinoma CGPLBR34Breast cfDNA Preoperative 60 F II NA Breast Infiltrating NA None 4.423.61 23.61 Y N N Cancer treatment naive Lobular Carcinoma CGPLBR35Breast cfDNA Preoperative 43 F II NA Breast Ductal NA None 4.5 22.5822.58 Y N N Cancer treatment naive Carcinoma insitu with MicroinvasionCGPLBR36 Breast cfDNA Preoperative 36 F II NA Breast Infiltrating NANone 4.4 17.73 17.73 Y N N Cancer treatment naive Ductal CarcinomaCGPLBR37 Breast cfDNA Preoperative 58 F II NA Breast Infiltrating NANone 4.4 9.39 9.39 Y N N Cancer treatment naive Ductal CarcinomaCGPLBR38 Breast cfDNA Preoperative 54 F I T1N0M0 Left BreastInfiltrating Moderate None 4.0 5.77 5.77 Y Y Y Cancer treatment naiveDuctal Carcinoma CGPLBR40 Breast cfDNA Preoperative 66 F III T2N2M0 LeftBreast Infiltrating Poor None 4.6 15.69 15.69 Y Y Y Cancer treatmentnaive Ductal Carcinoma CGPLBR41 Breast cfDNA Preoperative 51 F IIIT3N1M0 Left Breast Infiltrating Moderate None 4.5 11.56 11.56 Y N YCancer treatment naive Ductal Carcinoma CGPLBR45 Breast cfDNAPreoperative 57 F II NA Breast Infiltrating NA None 4.5 20.36 20.36 Y NN Cancer treatment naive Ductal Carcinoma CGPLBR46 Breast cfDNAPreoperative 54 F III NA Breast Infiltrating NA None 3.5 20.17 20.17 Y NN Cancer treatment naive Ductal Carcinoma CGPLBR47 Breast cfDNAPreoperative 54 F I NA Breast Infiltrating NA None 4.5 13.89 13.89 Y N NCancer treatment naive Ductal Carcinoma CGPLBR48 Breast cfDNAPreoperative 47 F II T2N1M0 Left Breast Infiltrating Poor None 3.9 7.077.07 Y Y Y Cancer treatment naive Ductal Carcinoma CGPLBR49 Breast cfDNAPreoperative 37 F II T2N1M0 Left Breast Infiltrating Poor None 4.0 5.745.74 Y N Y Cancer treatment naive Ductal Carcinoma CGPLBR50 Breast cfDNAPreoperative 51 F I NA Breast Infiltrating NA None 4.5 45.58 27.78 Y N NCancer treatment naive Ductal Carcinoma CGPLBR51 Breast cfDNAPreoperative 53 F II NA Breast Infiltrating NA None 4.0 8.83 8.83 Y N NCancer treatment naive Ductal Carcinoma CGPLBR52 Breast cfDNAPreoperative 68 F III NA Breast Infiltrating NA None 4.5 80.71 27.78 Y NN Cancer treatment naive Ductal Carcinoma CGPLBR55 Breast cfDNAPreoperative 53 F III T3N1M0 Right Breast Infiltrating Poor None 4.34.57 4.57 Y Y Y Cancer treatment naive Ductal Carcinoma CGPLBR56 BreastcfDNA Preoperative 56 F II NA Breast Infiltrating NA None 4.5 22.1622.16 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR57 BreastcfDNA Preoperative 54 F III T2N2M0 Left Breast Infiltrating NA None 4.34.02 4.02 Y N Y Cancer treatment naive Ductal Carcinoma CGPLBR59 BreastcfDNA Preoperative 42 F I T1N0M0 Left Breast Infiltrating Moderate None4.1 8.24 8.24 Y N Y Cancer treatment naive Ductal Carcinoma CGPLBR60Breast cfDNA Preoperative 61 F II NA Left Breast Infiltrating NA None4.5 11.09 11.09 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR61Breast cfDNA Preoperative 67 F II T2N1M0 Left Breast InfiltratingModerate None 4.1 13.25 13.25 Y N Y Cancer treatment naive DuctalCarcinoma CGPLBR63 Breast cfDNA Preoperative 48 F II T2N1M0 Left BreastInfiltrating Moderate None 4.0 6.19 6.19 Y Y Y Cancer treatment naiveDuctal Carcinoma CGPLBR65 Breast cfDNA Preoperative 50 F II NA LeftBreast Infiltrating NA None 3.5 41.75 35.71 Y N N Cancer treatment naiveDuctal Carcinoma CGPLBR68 Breast cfDNA Preoperative 64 F III T4N1M0Breast Infiltrating Poor None 3.4 10.41 10.41 Y N Y Cancer treatmentnaive Ductal Carcinoma CGPLBR69 Breast cfDNA Preoperative 43 F II T2N0M0Breast Infiltrating Moderate None 4.4 4.07 4.07 Y Y Y Cancer treatmentnaive Ductal Carcinoma CGPLBR70 Breast cfDNA Preoperative 60 F II T2N1M0Breast Infiltrating Moderate None 3.4 11.94 11.94 Y Y Y Cancer treatmentnaive Ductal Carcinoma CGPLBR71 Breast cfDNA Preoperative 65 F II T2N0M0Breast Infiltrating Poor None 3.1 7.64 7.64 Y Y Y Cancer treatment naiveDuctal Carcinoma CGPLBR72 Breast cfDNA Preoperative 67 F II T2N0M0Breast Infiltrating Well None 3.9 4.43 4.43 Y Y Y Cancer treatment naiveDuctal Carcinoma CGPLBR73 Breast cfDNA Preoperative 60 F II T2N1M0Breast Infiltrating Moderate None 3.3 14.69 14.69 Y Y Y Cancer treatmentnaive Ductal Carcinoma CGPLBR76 Breast cfDNA Preoperative 53 F II T2N0M0Right Breast Infiltrating Well None 4.9 8.71 8.71 Y Y Y Cancer treatmentnaive Ductal Carcinoma CGPLBR81 Breast cfDNA Preoperative 54 F II NABreast Infiltrating NA None 2.5 83.14 50.00 Y N N Cancer treatment naiveDuctal Carcinoma CGPLBR82 Breast cfDNA Preoperative 70 F I T1N0M0 RightBreast Infiltrating Moderate None 4.8 23.39 23.39 Y N Y Cancer treatmentnaive Lobular Carcinoma CGPLBR83 Breast cfDNA Preoperative 53 F IIT2N1M0 Right Breast Infiltrating Moderate None 3.7 100.17 100.17 Y Y YCancer treatment naive Ductal Carcinoma CGPLBR84 Breast cfDNAPreoperative NA F III NA Breast Infiltrating NA NA 3.6 16.95 16.95 Y N NCancer treatment naive Ductal Carcinoma CGPLBR87 Breast cfDNAPreoperative 80 F II T2N1M0 Right Breast Papilary Well None 3.6 277.3969.44 Y Y Y Cancer treatment naive Carcinoma CGPLBR88 Breast cfDNAPreoperative 48 F II T1N1M0 Left Breast Infiltrating Poor None 3.6 49.7549.75 Y Y Y Cancer treatment naive Ductal Carcinoma CGPLBR90 BreastcfDNA Preoperative 51 F II NA Right Breast Infiltrating NA None 3.014.24 14.24 Y N N Cancer treatment naive Ductal Carcinoma CGPLBR91Breast cfDNA Preoperative 62 F III T2N2M0 Breast Infiltrating Poor None3.2 22.41 22.41 Y N Y Cancer treatment naive Lobular Carcinoma CGPLBR92Breast cfDNA Preoperative 58 F II T2N1M0 Breast Infiltrating Poor None3.1 81.00 81.00 Y Y Y Cancer treatment naive Meduilary CarcinomaCGPLBR93 Breast cfDNA Preoperative 59 F II T1N0M0 Breast InfiltratingModerate None 3.3 27.94 27.94 Y N Y Cancer treatment naive DuctalCarcinoma CGPLH189 Healthy cfDNA Preoperative 74 M NA NA NA NA NA NA 5.05.84 5.84 Y N N treatment naive CGPLH190 Healthy cfDNA Preoperative 67 MNA NA NA NA NA NA 4.7 18.07 18.07 Y N N treatment naive CGPLH192 HealthycfDNA Preoperative 74 M NA NA NA NA NA NA 4.7 12.19 12.19 Y N Ntreatment naive CGPLH193 Healthy cfDNA Preoperative 72 F NA NA NA NA NANA 5.0 5.47 5.47 Y N N treatment naive CGPLH194 Healthy cfDNAPreoperative 75 F NA NA NA NA NA NA 5.0 9.98 9.98 Y N N treatment naiveCGPLH196 Healthy cfDNA Preoperative 64 M NA NA NA NA NA NA 5.0 11.6911.69 Y N N treatment naive CGPLH197 Healthy cfDNA Preoperative 74 M NANA NA NA NA NA 5.0 5.69 5.69 Y N N treatment naive CGPLH198 HealthycfDNA Preoperative 66 M NA NA NA NA NA NA 5.0 4.36 4.36 Y N N treatmentnaive CGPLH199 Healthy cfDNA Preoperative 75 F NA NA NA NA NA NA 5.09.77 9.77 Y N N treatment naive CGPLH200 Healthy cfDNA Preoperative 51 MNA NA NA NA NA NA 5.0 5.60 5.60 Y N N treatment naive CGPLH201 HealthycfDNA Preoperative 68 F NA NA NA NA NA NA 5.0 8.82 8.82 Y N N treatmentnaive CGPLH202 Healthy cfDNA Preoperative 73 M NA NA NA NA NA NA 5.05.54 5.54 Y N N treatment naive CGPLH203 Healthy cfDNA Preoperative 59 MNA NA NA NA NA NA 5.0 9.03 9.03 Y N N treatment naive CGPLH205 HealthycfDNA Preoperative 68 F NA NA NA NA NA NA 5.0 4.74 4.74 Y N N treatmentnaive CGPLH208 Healthy cfDNA Preoperative 75 F NA NA NA NA NA NA 5.04.67 4.67 Y N N treatment naive CGPLH209 Healthy cfDNA Preoperative 74 MNA NA NA NA NA NA 5.0 5.15 5.15 Y N N treatment naive CGPLH210 HealthycfDNA Preoperative 75 M NA NA NA NA NA NA 5.0 5.41 5.41 Y N N treatmentnaive CGPLH211 Healthy cfDNA Preoperative 75 F NA NA NA NA NA NA 5.06.24 6.24 Y N N treatment naive CGPLH300 Hettithy cfDNA Preoperative 72F NA NA NA NA NA NA 4.4 6.75 6.75 Y N N treatment naive CGPLH307 HealthycfDNA Preoperative 53 M NA NA NA NA NA NA 4.5 3.50 3.50 Y N N treatmentnaive CGPLH308 Healthy cfDNA Preoperative 60 M NA NA NA NA NA NA 4.56.01 6.01 Y N N treatment naive CGPLH309 Healthy cfDNA Preoperative 61 FNA NA NA NA NA NA 4.5 5.21 5.21 Y N N treatment naive CGPLH310 HealthycfDNA Preoperative 55 F NA NA NA NA NA NA 4.5 15.25 15.25 Y N Ntreatment naive CGPLH311 Healthy cfDNA Preoperative 50 M NA NA NA NA NANA 4.5 4.47 4.47 Y N N treatment naive CGPLH314 Healthy cfDNAPreoperative 59 M NA NA NA NA NA NA 4.5 9.62 9.62 Y N N treatment naiveCGPLH314 Healthy cfDNA, Preoperative 59 M NA NA NA NA NA NA 4.4 16.2416.24 Y N N technical treatment naive replicate CGPLH315 Healthy cfDNAPreoperative 59 F NA NA NA NA NA NA 4.2 11.55 11.55 Y N N treatmentnaive CGPLH316 Healthy cfDNA Preoperative 64 M NA NA NA NA NA NA 4.528.92 27.79 Y N N treatment naive CGPLH317 Healthy cfDNA Preoperative 53F NA NA NA NA NA NA 4.5 7.62 7.62 Y N N treatment naive CGPLH319 HealthycfDNA Preoperative 60 F NA NA NA NA NA NA 4.2 4.41 4.41 Y N N treatmentnaive CGPLH320 Healthy cfDNA Preoperative 75 F NA NA NA NA NA NA 4.56.93 6.93 Y N N treatment naive CGPLH322 Healthy cfDNA Preoperative 53 FNA NA NA NA NA NA 4.2 8.17 8.17 Y N N treatment naive CGPLH324 HealthycfDNA Preoperative 59 F NA NA NA NA NA NA 5.0 6.63 6.63 Y N N treatmentnaive CGPLH325 Healthy cfDNA Preoperative 54 M NA NA NA NA NA NA 4.64.15 4.15 Y N N treatment naive CGPLH326 Healthy cfDNA Preoperative 67 FNA NA NA NA NA NA 4.5 6.06 6.06 Y N N treatment naive CGPLH327 HealthycfDNA Preoperative 50 M NA NA NA NA NA NA 4.8 1.24 1.24 Y N N treatmentnaive CGPLH328 Healthy cfDNA, Preoperative 68 F NA NA NA NA NA NA 4.43.42 3.42 Y N N technical treatment naive replicate CGPLH328 HealthycfDNA Preoperative 68 F NA NA NA NA NA NA 4.9 5.47 5.47 Y N N treatmentnaive CGPLH329 Healthy cfDNA Preoperative 59 M NA NA NA NA NA NA 4.55.27 5.27 Y N N treatment naive CGPLH330 Healthy cfDNA Preoperative 75 MNA NA NA NA NA NA 4.3 10.21 10.21 Y N N treatment naive CGPLH331 HealthycfDNA Preoperative 55 M NA NA NA NA NA NA 4.6 2.63 2.63 Y N N treatmentnaive CGPLH331 Healthy cfDNA, Preoperative 55 M NA NA NA NA NA NA 4.34.15 4.15 Y N N technical treatment naive replicate CGPLH333 HealthycfDNA Preoperative 60 M NA NA NA NA NA NA 4.7 4.06 4.06 Y N N treatmentnaive CGPLH335 Healthy cfDNA Preoperative 74 M NA NA NA NA NA NA 4.49.39 9.39 Y N N treatment naive CGPLH336 Healthy cfDNA Preoperative 53 FNA NA NA NA NA NA 4.6 6.64 6.64 Y N N treatment naive CGPLH337 HealthycfDNA Preoperative 53 F NA NA NA NA NA NA 4.2 4.48 4.48 Y N N treatmentnaive CGPLH338 Healthy cfDNA Preoperative 75 M NA NA NA NA NA NA 4.559.44 59.44 Y N N treatment naive CGPLH339 Healthy cfDNA Preoperative 70M NA NA NA NA NA NA 4.5 12.27 12.27 Y N N treatment naive CGPLH340Healthy cfDNA Preoperative 62 M NA NA NA NA NA NA 4.5 4.86 4.86 Y N Ntreatment naive CGPLH341 Healthy cfDNA Preoperative 61 F NA NA NA NA NANA 4.1 7.62 7.62 Y N N treatment naive CGPLH342 Healthy cfDNAPreoperative 49 F NA NA NA NA NA NA 4.2 18.29 18.29 Y N N treatmentnaive CGPLH343 Healthy cfDNA Preoperative 58 M NA NA NA NA NA NA 4.53.49 3.49 Y N N treatment naive CGPLH344 Healthy cfDNA Preoperative 50 MNA NA NA NA NA NA 4.2 8.41 8.41 Y N N treatment naive CGPLH345 HealthycfDNA Preoperative 55 F NA NA NA NA NA NA 4.5 9.73 9.73 Y N N treatmentnaive CGPLH346 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.57.86 7.86 Y N N treatment naive CGPLH35 Healthy cfDNA Preoperative 48 FNA NA NA NA NA NA 4.0 13.15 13.15 Y N Y treatment naive CGPLH350 HealthycfDNA Preoperative 65 M NA NA NA NA NA NA 3.5 6.09 6.09 Y N N treatmentnaive CGPLH351 Healthy cfDNA Preoperative 71 M NA NA NA NA NA NA 4.015.91 15.91 Y N N treatment naive CGPLH352 Healthy cfDNA Preoperative 50F NA NA NA NA NA NA 4.2 6.47 6.47 Y N N treatment naive CGPLH353 HealthycfDNA Preoperative 50 F NA NA NA NA NA NA 4.2 4.47 4.47 Y N N treatmentnaive CGPLH354 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.217.49 17.49 Y N N treatment naive CGPLH355 Healthy cfDNA Preoperative 70M NA NA NA NA NA NA 4.2 11.58 11.58 Y N N treatment naive CGPLH356Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.5 3.84 3.84 Y N Ntreatment naive CGPLH357 Healthy cfDNA Preoperative 52 F NA NA NA NA NANA 4.2 11.79 11.79 Y N N treatment naive CGPLH358 Healthy cfDNAPreoperative 55 M NA NA NA NA NA NA 4.2 21.08 21.08 Y N N treatmentnaive CGPLH36 Healthy cfDNA Preoperative 36 F NA NA NA NA NA NA 4.013.00 13.00 Y N Y treatment naive CGPLH360 Healthy cfDNA Preoperative 60M NA NA NA NA NA NA 4.2 3.48 3.48 Y N N treatment naive CGPLH361 HealthycfDNA Preoperative 50 M NA NA NA NA NA NA 4.3 6.98 6.98 Y N N treatmentnaive CGPLH362 Healthy cfDNA Preoperative 72 F NA NA NA NA NA NA 4.48.49 8.49 Y N N treatment naive CGPLH363 Healthy cfDNA Preoperative 68 FNA NA NA NA NA NA 4.5 4.44 4.44 Y N N treatment naive CGPLH364 HealthycfDNA Preoperative 50 F NA NA NA NA NA NA 4.5 17.31 17.31 Y N Ntreatment naive CGPLH365 Healthy cfDNA Preoperative 68 F NA NA NA NA NANA 4.5 0.55 0.55 Y N N treatment naive CGPLH366 Healthy cfDNAPreoperative 61 M NA NA NA NA NA NA 4.5 4.88 4.88 Y N N treatment naiveCGPLH367 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.4 6.48 6.48Y N N treatment naive CGPLH368 Healthy cfDNA Preoperative 50 M NA NA NANA NA NA 4.3 2.53 2.53 Y N N treatment naive CGPLH369 Healthy cfDNAPreoperative 55 F NA NA NA NA NA NA 4.3 10.18 10.18 Y N N treatmentnaive CGPLH369 Healthy cfDNA, Preoperative 55 F NA NA NA NA NA NA 4.410.71 10.71 Y N N technical treatment naive replicate CGPLH37 HealthycfDNA Preoperative 39 F NA NA NA NA NA NA 4.0 9.73 9.73 Y N Y treatmentnaive CGPLH370 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.57.22 7.22 Y N N treatment naive CGPLH371 Healthy cfDNA Preoperative 57 FNA NA NA NA NA NA 4.6 5.62 5.62 Y N N treatment naive CGPLH380 HealthycfDNA Preoperative 53 F NA NA NA NA NA NA 4.2 6.61 6.61 Y N N treatmentnaive CGPLH381 Healthy cfDNA Preoperative 56 F NA NA NA NA NA NA 4.227.38 27.38 Y N N treatment naive CGPLH382 Healthy cfDNA Preoperative 53F NA NA NA NA NA NA 4.5 11.58 11.58 Y N N treatment naive CGPLH383Healthy cfDNA Preoperative 62 F NA NA NA NA NA NA 4.5 25.50 25.50 Y N Ntreatment naive CGPLH384 Healthy cfDNA Preoperative 50 M NA NA NA NA NANA 4.5 15.66 15.66 Y N N treatment naive CGPLH385 Healthy cfDNAPreoperative 69 M NA NA NA NA NA NA 4.5 19.35 19.35 Y N N treatmentnaive CGPLH386 Healthy cfDNA Preoperative 62 M NA NA NA NA NA NA 4.56.46 6.46 Y N N treatment naive CGPLH386 Healthy cfDNA, Preoperative 62M NA NA NA NA NA NA 4.6 6.54 6.54 Y N N technical treatment naivereplicate CGPLH387 Healthy cfDNA Preoperative 71 F NA NA NA NA NA NA 4.56.19 6.19 Y N N treatment naive CGPLH388 Healthy cfDNA Preoperative 57 FNA NA NA NA NA NA 4.5 6.62 6.62 Y N N treatment naive CGPLH389 HealthycfDNA Preoperative 73 F NA NA NA NA NA NA 4.6 14.78 14.78 Y N Ntreatment naive CGPLH390 Healthy cfDNA Preoperative 50 F NA NA NA NA NANA 4.5 12.14 12.14 Y N N treatment naive CGPLH391 Healthy cfDNAPreoperative 58 M NA NA NA NA NA NA 4.5 8.88 8.88 Y N N treatment naiveCGPLH391 Healthy cfDNA, Preoperative 58 M NA NA NA NA NA NA 4.5 8.378.37 Y N N technical treatment naive replicate CGPLH392 Healthy cfDNAPreoperative 57 F NA NA NA NA NA NA 4.5 8.39 8.39 Y N N treatment naiveCGPLH393 Healthy cfDNA Preoperative 54 M NA NA NA NA NA NA 4.5 5.27 5.27Y N N treatment naive CGPLH394 Healthy cfDNA Preoperative 55 F NA NA NANA NA NA 4.4 3.79 3.79 Y N N treatment naive CGPLH395 Healthy cfDNAPreoperative 56 F NA NA NA NA NA NA 4.4 9.56 9.56 Y N N treatment naiveCGPLH395 Healthy cfDNA, Preoperative 56 F NA NA NA NA NA NA 4.4 5.405.40 Y N N technical treatment naive replicate CGPLH396 Healthy cfDNAPreoperative 50 M NA NA NA NA NA NA 4.4 20.31 20.31 Y N N treatmentnaive CGPLH398 Healthy cfDNA Preoperative 68 M NA NA NA NA NA NA 4.313.01 13.01 Y N N treatment naive CGPLH399 Healthy cfDNA Preoperative 62F NA NA NA NA NA NA 4.4 4.79 4.79 Y N N treatment naive CGPLH400 HealthycfDNA Preoperative 64 M NA NA NA NA NA NA 4.4 7.70 7.70 Y N N treatmentnaive CGPLH400 Healthy cfDNA, Preoperative 64 M NA NA NA NA NA NA 4.46.26 6.26 Y N N technical treatment naive replicate CGPLH401 HealthycfDNA Preoperative 50 M NA NA NA NA NA NA 4.3 13.01 13.01 Y N Ntreatment naive CGPLH401 Healthy cfDNA, Preoperative 50 M NA NA NA NA NANA 4.4 11.13 11.13 Y N N technical treatment naive replicate CGPLH402Healthy cfDNA Preoperative 57 F NA NA NA NA NA NA 4.5 2.89 2.89 Y N Ntreatment naive CGPLH403 Healthy cfDNA Preoperative 64 M NA NA NA NA NANA 4.3 4.41 4.41 Y N N treatment naive CGPLH404 Healthy cfDNAPreoperative 50 M NA NA NA NA NA NA 4.2 6.38 6.38 Y N N treatment naiveCGPLH405 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.4 7.28 7.28Y N N treatment naive CGPLH406 Healthy cfDNA Preoperative 57 M NA NA NANA NA NA 4.2 5.40 5.40 Y N N treatment naive CGPLH407 Healthy cfDNAPreoperative 75 F NA NA NA NA NA NA 4.0 13.30 13.30 Y N N treatmentnaive CGPLH408 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.25.18 5.18 Y N N treatment naive CGPLH409 Healthy cfDNA Preoperative 53 MNA NA NA NA NA NA 3.7 3.98 3.98 Y N N treatment naive CGPLH410 HealthycfDNA Preoperative 52 M NA NA NA NA NA NA 4.1 6.91 6.91 Y N N treatmentnaive CGPLH411 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.13.30 3.30 Y N N treatment naive CGPLH412 Healthy cfDNA Preoperative 53 FNA NA NA NA NA NA 4.1 5.55 5.55 Y N N treatment naive CGPLH413 HealthycfDNA Preoperative 54 F NA NA NA NA NA NA 4.5 8.18 8.18 Y N N treatmentnaive CGPLH414 Healthy cfDNA Preoperative 56 M NA NA NA NA NA NA 3.85.85 5.85 Y N N treatment naive CGPLH415 Healthy cfDNA Preoperative 59 MNA NA NA NA NA NA 4.7 10.20 10.20 Y N N treatment naive CGPLH416 HealthycfDNA Preoperative 58 F NA NA NA NA NA NA 4.5 11.73 11.73 Y N Ntreatment naive CGPLH417 Healthy cfDNA Preoperative 70 M NA NA NA NA NANA 4.2 10.98 10.98 Y N N treatment naive CGPLH418 Healthy cfDNAPreoperative 70 F NA NA NA NA NA NA 4.5 10.96 10.96 Y N N treatmentnaive CGPLH419 Healthy cfDNA Preoperative 65 F NA NA NA NA NA NA 4.510.17 10.17 Y N N treatment naive CGPLH42 Healthy cfDNA Preoperative 54F NA NA NA NA NA NA 4.0 14.30 14.30 Y N Y treatment naive CGPLH420Healthy cfDNA Preoperative 51 M NA NA NA NA NA NA 4.2 12.32 12.32 Y N Ntreatment naive CGPLH422 Healthy cfDNA Preoperative 68 F NA NA NA NA NANA 4.6 5.42 5.42 Y N N treatment naive CGPLH423 Healthy cfDNAPreoperative 54 M NA NA NA NA NA NA 4.2 2.85 2.85 Y N N treatment naiveCGPLH424 Healthy cfDNA Preoperative 53 F NA NA NA NA NA NA 4.7 1.66 1.66Y N N treatment naive CGPLH425 Healthy cfDNA Preoperative 53 F NA NA NANA NA NA 4.4 5.98 5.98 Y N N treatment naive CGPLH426 Healthy cfDNAPreoperative 68 M NA NA NA NA NA NA 4.4 2.84 2.84 Y N N treatment naiveCGPLH427 Healthy cfDNA Preoperative 68 M NA NA NA NA NA NA 4.4 10.8610.86 Y N N treatment naive CGPLH428 Healthy cfDNA Preoperative 50 F NANA NA NA NA NA 4.5 6.27 6.27 Y N N treatment naive CGPLH429 HealthycfDNA Preoperative 63 F NA NA NA NA NA NA 4.5 3.89 3.89 Y N N treatmentnaive CGPLH43 Healthy cfDNA Preoperative 49 F NA NA NA NA NA NA 4.0 8.508.50 Y N Y treatment naive CGPLH430 Healthy cfDNA Preoperative 69 F NANA NA NA NA NA 4.2 10.33 10.33 Y N N treatment naive CGPLH431 HealthycfDNA Preoperative 59 F NA NA NA NA NA NA 4.8 12.81 12.81 Y N Ntreatment naive CGPLH432 Healthy cfDNA Preoperative 59 F NA NA NA NA NANA 4.8 2.42 2.42 Y N N treatment naive CGPLH434 Healthy cfDNAPreoperative 59 M NA NA NA NA NA NA 4.6 8.83 8.83 Y N N treatment naiveCGPLH435 Healthy cfDNA Preoperative 50 M NA NA NA NA NA NA 4.5 8.95 8.95Y N N treatment naive CGPLH436 Healthy cfDNA Preoperative 50 F NA NA NANA NA NA 4.5 4.29 4.29 Y N N treatment naive CGPLH437 Healthy cfDNAPreoperative 56 M NA NA NA NA NA NA 4.6 18.07 18.07 Y N N treatmentnaive CGPLH438 Healthy cfDNA Preoperative 69 M NA NA NA NA NA NA 4.816.62 16.62 Y N N treatment naive CGPLH439 Healthy cfDNA Preoperative 50F NA NA NA NA NA NA 4.7 4.38 4.38 Y N N treatment naive CGPLH440 HealthycfDNA Preoperative 72 M NA NA NA NA NA NA 4.7 4.32 4.32 Y N N treatmentnaive CGPLH441 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.77.80 7.80 Y N N treatment naive CGPLH442 Healthy cfDNA Preoperative 59 FNA NA NA NA NA NA 4.5 6.15 6.15 Y N N treatment naive CGPLH443 HealthycfDNA Preoperative 52 F NA NA NA NA NA NA 4.4 3.44 3.44 Y N N treatmentnaive CGPLH444 Healthy cfDNA Preoperative 60 F NA NA NA NA NA NA 4.44.12 4.12 Y N N treatment naive CGPLH445 Healthy cfDNA Preoperative 53 FNA NA NA NA NA NA 4.4 4.36 4.36 Y N N treatment naive CGPLH446 HealthycfDNA Preoperative 51 F NA NA NA NA NA NA 4.4 2.92 2.92 Y N N treatmentnaive CGPLH447 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.63.87 3.87 Y N N treatment naive CGPLH448 Healthy cfDNA Preoperative 51 FNA NA NA NA NA NA 4.4 5.29 5.29 Y N N treatment naive CGPLH449 HealthycfDNA Preoperative 51 F NA NA NA NA NA NA 4.5 3.77 3.77 Y N N treatmentnaive CGPLH45 Healthy cfDNA Preoperative 58 F NA NA NA NA NA NA 4.010.85 10.85 Y N Y treatment naive CGPLH450 Healthy cfDNA Preoperative 50F NA NA NA NA NA NA 4.5 5.62 5.62 Y N N treatment naive CGPLH451 HealthycfDNA Preoperative 54 F NA NA NA NA NA NA 4.6 7.24 7.24 Y N N treatmentnaive CGPLH452 Healthy cfDNA Preoperative 69 M NA NA NA NA NA NA 4.42.54 2.54 Y N N treatment naive CGPLH453 Healthy cfDNA Preoperative 53 FNA NA NA NA NA NA 4.6 9.11 9.11 Y N N treatment naive CGPLH455 HealthycfDNA Preoperative 55 F NA NA NA NA NA NA 4.4 2.64 2.64 Y N N treatmentnaive CGPLH455 Healthy cfDNA, Preoperative 55 F NA NA NA NA NA NA 4.52.42 2.42 Y N N technical treatment naive replicate CGPLH456 HealthycfDNA Preoperative 54 F NA NA NA NA NA NA 4.5 3.11 3.11 Y N N treatmentnaive CGPLH457 Healthy cfDNA Preoperative 54 F NA NA NA NA NA NA 4.45.92 5.92 Y N N treatment naive CGPLH458 Healthy cfDNA Preoperative 52 FNA NA NA NA NA NA 4.5 16.04 16.04 Y N N treatment naive CGPLH459 HealthycfDNA Preoperative 50 F NA NA NA NA NA NA 4.4 6.52 6.52 Y N N treatmentnaive CGPLH46 Healthy cfDNA Preoperative 35 F NA NA NA NA NA NA 4.0 8.258.25 Y N Y treatment naive CGPLH460 Healthy cfDNA Preoperative 50 F NANA NA NA NA NA 4.6 5.24 5.24 Y N N treatment naive CGPLH463 HealthycfDNA Preoperative 53 F NA NA NA NA NA NA 4.5 22.77 22.77 Y N Ntreatment naive CGPLH464 Healthy cfDNA Preoperative 50 F NA NA NA NA NANA 4.4 2.90 2.90 Y N N treatment naive CGPLH465 Healthy cfDNAPreoperative 50 F NA NA NA NA NA NA 4.5 4.76 4.76 Y N N treatment naiveCGPLH466 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.6 5.68 5.68Y N N treatment naive CGPLH466 Healthy cfDNA, Preoperative 50 F NA NA NANA NA NA 4.5 6.75 6.75 Y N N technical treatment naive replicateCGPLH467 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.5 4.59 4.59Y N N treatment naive CGPLH468 Healthy cfDNA Preoperative 53 M NA NA NANA NA NA 4.5 11.19 11.19 Y N N treatment naive CGPLH469 Healthy cfDNAPreoperative 50 F NA NA NA NA NA NA 4.5 3.25 3.25 Y N N treatment naiveCGPLH47 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.0 7.43 7.43Y N Y treatment naive CGPLH470 Healthy cfDNA Preoperative 68 F NA NA NANA NA NA 4.5 13.64 13.64 Y N N treatment naive CGPLH471 Healthy cfDNAPreoperative 70 F NA NA NA NA NA NA 4.3 13.00 13.00 Y N N treatmentnaive CGPLH472 Healthy cfDNA Preoperative 69 F NA NA NA NA NA NA 4.210.17 10.17 Y N N treatment naive CGPLH473 Healthy cfDNA Preoperative 62M NA NA NA NA NA NA 4.3 2.98 2.98 Y N N treatment naive CGPLH474 HealthycfDNA Preoperative 63 M NA NA NA NA NA NA 4.3 29.15 29.15 Y N Ntreatment naive CGPLH475 Healthy cfDNA Preoperative 67 F NA NA NA NA NANA 4.0 7.26 7.26 Y N N treatment naive CGPLH476 Healthy cfDNAPreoperative 65 F NA NA NA NA NA NA 4.3 6.16 6.16 Y N N treatment naiveCGPLH477 Healthy cfDNA Preoperative 61 F NA NA NA NA NA NA 4.3 15.2115.21 Y N N treatment naive CGPLH478 Healthy cfDNA Preoperative 51 F NANA NA NA NA NA 4.4 7.29 7.29 Y N N treatment naive CGPLH479 HealthycfDNA Preoperative 52 M NA NA NA NA NA NA 4.5 8.73 8.73 Y N N treatmentnaive CGPLH48 Healthy cfDNA Preoperative 38 F NA NA NA NA NA NA 4.0 6.386.38 Y N Y treatment naive CGPLH480 Healthy cfDNA Preoperative 50 F NANA NA NA NA NA 4.4 10.62 10.62 Y N N treatment naive CGPLH481 HealthycfDNA Preoperative 53 F NA NA NA NA NA NA 4.3 6.75 6.75 Y N N treatmentnaive CGPLH482 Healthy cfDNA Preoperative 50 M NA NA NA NA NA NA 4.323.58 23.58 Y N N treatment naive CGPLH483 Healthy cfDNA Preoperative 66M NA NA NA NA NA NA 4.4 14.44 14.44 Y N N treatment naive CGPLH484Healthy cfDNA Preoperative 72 M NA NA NA NA NA NA 4.2 14.32 14.32 Y N Ntreatment naive CGPLH485 Healthy cfDNA Preoperative 50 F NA NA NA NA NANA 4.3 9.64 9.64 Y N N treatment naive CGPLH486 Healthy cfDNAPreoperative 50 F NA NA NA NA NA NA 4.3 10.16 10.16 Y N N treatmentnaive CGPLH487 Healthy cfDNA Preoperative 50 M NA NA NA NA NA NA 4.46.11 6.11 Y N N treatment naive CGPLH488 Healthy cfDNA Preoperative 50 FNA NA NA NA NA NA 4.5 7.88 7.88 Y N N treatment naive CGPLH49 HealthycfDNA Preoperative 39 F NA NA NA NA NA NA 4.0 6.60 6.60 Y N Y treatmentnaive CGPLH490 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.54.18 4.18 Y N N treatment naive CGPLH491 Healthy cfDNA Preoperative 50 FNA NA NA NA NA NA 4.5 13.16 13.16 Y N N treatment naive CGPLH492 HealthycfDNA Preoperative 51 F NA NA NA NA NA NA 4.5 3.83 3.83 Y N N treatmentnaive CGPLH493 Healthy cfDNA Preoperative 64 M NA NA NA NA NA NA 4.525.06 25.06 Y N N treatment naive CGPLH494 Healthy cfDNA Preoperative 53F NA NA NA NA NA NA 4.4 5.24 5.24 Y N N treatment naive CGPLH495 HealthycfDNA Preoperative 50 F NA NA NA NA NA NA 4.4 5.03 5.03 Y N N treatmentnaive CGPLH496 Healthy cfDNA Preoperative 74 M NA NA NA NA NA NA 4.534.01 27.78 Y N N treatment naive CGPLH497 Healthy cfDNA Preoperative 68F NA NA NA NA NA NA 4.5 8.24 8.24 Y N N treatment naive CGPLH497 HealthycfDNA, Preoperative 68 F NA NA NA NA NA NA 4.4 5.88 5.88 Y N N technicaltreatment naive replicate CGPLH498 Healthy cfDNA Preoperative 54 F NA NANA NA NA NA 4.4 5.33 5.33 Y N N treatment naive CGPLH499 Healthy cfDNAPreoperative 52 F NA NA NA NA NA NA 4.5 7.85 7.85 Y N N treatment naiveCGPLH50 Healthy cfDNA Preoperative 55 F NA NA NA NA NA NA 4.0 7.05 7.05Y N Y treatment naive CGPLH500 Healthy cfDNA Preoperative 51 F NA NA NANA NA NA 4.5 3.49 3.49 Y N N treatment naive CGPLH501 Healthy cfDNAPreoperative 50 F NA NA NA NA NA NA 4.3 6.29 6.29 Y N N treatment naiveCGPLH502 Healthy cfDNA Preoperative 53 F NA NA NA NA NA NA 4.5 2.24 2.24Y N N treatment naive CGPLH503 Healthy cfDNA Preoperative 67 M NA NA NANA NA NA 4.5 11.01 11.01 Y N N treatment naive CGPLH504 Healthy cfDNAPreoperative 57 F NA NA NA NA NA NA 4.3 6.60 6.60 Y N N treatment naiveCGPLH504 Healthy cfDNA, Preoperative 57 F NA NA NA NA NA NA 4.2 10.0210.02 Y N N technical treatment naive replicate CGPLH505 Healthy cfDNAPreoperative 50 F NA NA NA NA NA NA 4.1 5.23 5.23 Y N N treatment naiveCGPLH506 Healthy cfDNA Preoperative 51 F NA NA NA NA NA NA 4.5 12.2312.23 Y N N treatment naive CGPLH507 Healthy cfDNA Preoperative 56 F NANA NA NA NA NA 4.1 9.89 9.89 Y N N treatment naive CGPLH508 HealthycfDNA Preoperative 54 M NA NA NA NA NA NA 4.5 8.66 8.66 Y N N treatmentnaive CGPLH508 Healthy cfDNA, Preoperative 54 F NA NA NA NA NA NA 4.49.55 9.55 Y N N technical treatment naive replicate CGPLH509 HealthycfDNA Preoperative 60 M NA NA NA NA NA NA 4.0 9.79 9.79 Y N N treatmentnaive CGPLH51 Healthy cfDNA Preoperative 48 F NA NA NA NA NA NA 4.0 7.857.85 Y N Y treatment naive CGPLH510 Healthy cfDNA Preoperative 67 M NANA NA NA NA NA 4.2 14.20 14.20 Y N N treatment naive CGPLH511 HealthycfDNA Preoperative 75 M NA NA NA NA NA NA 4.5 12.94 12.94 Y N Ntreatment naive CGPLH512 Healthy cfDNA Preoperative 52 M NA NA NA NA NANA 4.3 8.60 8.60 Y N N treatment naive CGPLH513 Healthy cfDNAPreoperative 57 M NA NA NA NA NA NA 4.3 6.54 6.54 Y N N treatment naiveCGPLH514 Healthy cfDNA Preoperative 55 F NA NA NA NA NA NA 4.4 10.9410.94 Y N N treatment naive CGPLH515 Healthy cfDNA Preoperative 68 F NANA NA NA NA NA 4.5 8.71 8.71 Y N N treatment naive CGPLH516 HealthycfDNA Preoperative 65 F NA NA NA NA NA NA 4.5 7.32 7.32 Y N N treatmentnaive CGPLH517 Healthy cfDNA Preoperative 54 F NA NA NA NA NA NA 4.65.16 5.16 Y N N treatment naive CGPLH517 Healthy cfDNA, Preoperative 54F NA NA NA NA NA NA 4.5 9.74 9.74 Y N N technical treatment naivereplicate CGPLH518 Healthy cfDNA Preoperative 50 F NA NA NA NA NA NA 4.45.92 5.92 Y N N treatment naive CGPLH519 Healthy cfDNA Preoperative 54 MNA NA NA NA NA NA 4.4 6.96 6.96 Y N N treatment naive CGPLH52 HealthycfDNA Preoperative 40 F NA NA NA NA NA NA 4.0 9.90 9.90 Y N Y treatmentnaive CGPLH520 Healthy cfDNA Preoperative 51 F NA NA NA NA NA NA 4.38.27 8.27 Y N N treatment naive CGPLH54 Healthy cfDNA Preoperative 47 FNA NA NA NA NA NA 4.0 14.18 14.18 Y N Y treatment naive CGPLH55 HealthycfDNA Preoperative 46 F NA NA NA NA NA NA 4.0 7.35 7.35 Y N Y treatmentnaive CGPLH56 Healthy cfDNA Preoperative 42 F NA NA NA NA NA NA 4.0 5.205.20 Y N Y treatment naive CGPLH57 Healthy cfDNA Preoperative 39 F NA NANA NA NA NA 4.0 7.15 7.15 Y N Y treatment naive CGPLH59 Healthy cfDNAPreoperative 34 F NA NA NA NA NA NA 4.0 6.03 6.03 Y N Y treatment naiveCGPLH625 Healthy cfDNA Preoperative 53 F NA NA NA NA NA NA 4.5 2.64 2.64Y N N treatment naive CGPLH625 Healthy cfDNA Preoperative 53 F NA NA NANA NA NA 4.5 1.69 1.69 Y N N treatment naive CGPLH626 Healthy cfDNA,Preoperative 50 F NA NA NA NA NA NA 4.0 11.12 11.12 Y N N technicaltreatment naive replicate CGPLH63 Healthy cfDNA Preoperative 47 F NA NANA NA NA NA 4.0 10.10 10.10 Y N Y treatment naive CGPLH639 Healthy cfDNAPreoperative 50 F NA NA NA NA NA NA 4.5 2.00 2.00 Y N N treatment naiveCGPLH64 Healthy cfDNA Preoperative 55 F NA NA NA NA NA NA 4.0 8.03 8.03Y N Y treatment naive CGPLH640 Healthy cfDNA Preoperative 50 F NA NA NANA NA NA 4.5 9.36 9.36 Y N N treatment naive CGPLH642 Healthy cfDNAPreoperative 54 F NA NA NA NA NA NA 4.5 4.99 4.99 Y N N treatment naiveCGPLH643 Healthy cfDNA Preoperative 55 F NA NA NA NA NA NA 4.4 7.12 7.12Y N N treatment naive CGPLH644 Healthy cfDNA Preoperative 50 F NA NA NANA NA NA 4.4 5.06 5.06 Y N N treatment naive CGPLH646 Healthy cfDNAPreoperative 50 F NA NA NA NA NA NA 4.4 6.75 6.75 Y N N treatment naiveCGPLH75 Healthy cfDNA Preoperative 46 F NA NA NA NA NA NA 4.0 3.87 3.87Y N Y treatment naive CGPLH76 Healthy cfDNA Preoperative 53 F NA NA NANA NA NA 4.0 4.03 4.03 Y N Y treatment naive CGPLH77 Healthy cfDNAPreoperative 46 F NA NA NA NA NA NA 4.0 5.89 5.89 Y N Y treatment naiveCGPLH78 Healthy cfDNA Preoperative 34 F NA NA NA NA NA NA 4.0 2.51 2.51Y N Y treatment naive CGPLH79 Healthy cfDNA Preoperative 37 F NA NA NANA NA NA 4.0 3.68 3.68 Y N Y treatment naive CGPLH80 Healthy cfDNAPreoperative 37 F NA NA NA NA NA NA 4.0 1.94 1.94 Y N Y treatment naiveCGPLH81 Healthy cfDNA Preoperative 54 F NA NA NA NA NA NA 4.0 5.16 5.16Y N Y treatment naive CGPLH82 Healthy cfDNA Preoperative 38 F NA NA NANA NA NA 4.0 3.30 3.30 Y N Y treatment naive CGPLH83 Healthy cfDNAPreoperative 60 F NA NA NA NA NA NA 4.0 5.04 5.04 Y N Y treatment naiveCGPLH84 Healthy cfDNA Preoperative 45 F NA NA NA NA NA NA 4.0 3.33 3.33Y N Y treatment naive CGPLLU13 Lung cfDNA Pre-treatment, 72 F IVT1BN2bM1a Right Adenocarcinoma NA Bone 5.0 7.67 7.67 Y N Y Cancer Day 2Lung CGPLLU13 Lung cfDNA Post-treatment, 72 F IV T1BN2bM1a RightAdenocarcinoma NA Bone 4.5 8.39 8.39 Y N Y Cancer Day 5 Lung CGPLLU13Lung cfDNA Post-treatment, 72 F IV T1BN2bM1a Right Adenocarcinoma NABone 3.2 8.66 8.66 Y N Y Cancer Day 28 Lung CGPLLU13 Lung cfDNAPost-treatment, 72 F IV T1BN2bM1a Right Adenocarcinoma NA Bone 5.0 5.975.97 Y N Y Cancer Day 91 Lung CGPLLU14 Lung cfDNA Pre-treatment, 55 F IVT1N1M0 Right Lower Adenocarcinoma Moderate NA 2.0 2.55 2.55 Y N Y CancerDay −38 Lobe of Lung CGPLLU14 Lung cfDNA Pre-treatment, 55 F IV T1N1M0Right Lower Adenocarcinoma Moderate NA 2.0 2.55 2.55 Y N Y Cancer Day−16 Lobe of Lung CGPLLU14 Lung cfDNA Pre-treatment, 55 F IV T1N1M0 RightLower Adenocarcinoma Moderate NA 2.0 2.55 2.55 Y N Y Cancer Day −8 Lobeof Lung CGPLLU14 Lung cfDNA Pre-treatment, 55 F IV T1N1M0 Right LowerAdenocarcinoma Moderate NA 2.0 2.55 2.55 Y N Y Cancer Day 0 Lobe of LungCGPLLU14 Lung cfDNA Post-treatment, 55 F IV T1N1M0 Right LowerAdenocarcinoma Moderate NA 2.0 2.55 2.55 Y N Y Cancer Day 0.33 Lobe ofLung CGPLLU14 Lung cfDNA Post-treatment, 55 F IV T1N1M0 Right LowerAdenocarcinoma Moderate NA 2.0 2.55 2.55 Y N Y Cancer Day 7 Lobe of LungCGPLLU144 Lung cfDNA Preoperative 52 M II T2aN1M0 Lung AdenocarcinomaPoor None 3.5 31.51 31.51 Y Y Y Cancer treatment naive CGPLLU147 LungcfDNA Preoperative 60 M III T3N2M0 Lung Adenosquamous Poor None 3.8 6.726.72 Y Y Y Cancer treatment naive Carcinoma CGPLLU151 Lung cfDNAPreoperative 41 F II T3N2M0 Lung Adenocarcinoma Well None 4.0 83.0483.04 Y N Y Cancer treatment naive CGPLLU162 Lung cfDNA Preoperative 38M II T1N1M0 Right Adenocarcinoma Moderate None 3.1 40.32 40.32 Y Y YCancer treatment naive Lung CGPLLU163 Lung cfDNA Preoperative 66 M IIT1N1M0 Left Adenocarcinoma Poor None 5.0 54.03 54.03 Y Y Y Cancertreatment naive Lung CGPLLU165 Lung cfDNA Preoperative 68 F II T1N1M0Right Adenocarcinoma Well None 4.5 20.13 20.13 Y Y Y Cancer treatmentnaive Lung CGPLLU168 Lung cfDNA Preoperative 70 F I T2aN0M0 LungAdenocarcinoma Poor None 4.3 19.38 19.38 Y Y Y Cancer treatment naiveCGPLLU169 Lung cfDNA Preoperative 64 M I T1bN0M0 Lung Squamous CelModerate None 4.2 13.70 13.70 Y N Y Cancer treatment naive CarcinomaCGPLLU175 Lung cfDNA Preoperative 47 M I T2N0M0 Lung Squamous CelModerate None 4.4 16.84 16.84 Y Y Y Cancer treatment naive CarcinomaCGPLLU176 Lung cfDNA Preoperative 58 M I T2N0M0 Lung AdenosquamousModerate None 3.2 7.86 7.86 Y Y Y Cancer treatment naive CarcinomaCGPLLU177 Lung cfDNA Preoperative 45 M II T3N0M0 Right Adenocarcinoma NANone 3.9 19.07 19.07 Y Y Y Cancer treatment naive Lung CGPLLU180 LungcfDNA Preoperative 57 M I T2N0M0 Right Large Cel Poor None 3.2 19.3119.31 Y Y Y Cancer treatment naive Lung Carcinoma CGPLLU198 Lung cfDNAPreoperative 49 F I T2N0M0 Left Adenocarcinoma Moderate None 4.2 14.0914.09 Y Y Y Cancer treatment naive Lung CGPLLU202 Lung cfDNAPreoperative 68 M I T2aN0M0 Right Adenocarcinoma NA None 4.4 24.72 24.72Y Y Y Cancer treatment naive Lung CGPLLU203 Lung cfDNA Preoperative 68 MII T3N0M0 Right Squamous Cel Well None 4.2 26.24 26.24 Y N Y Cancertreatment naive Lung Carcinoma CGPLLU205 Lung cfDNA Preoperative 65 M IIT3N0M0 Left Adenocarcinoma Poor None 4.0 18.56 18.56 Y Y Y Cancertreatment naive Lung CGPLLU206 Lung cfDNA Preoperative 55 M III T3N1M0Right Squamous Cel Poor None 3.5 18.24 18.24 Y Y Y Cancer treatmentnaive Lung Carcinoma CGPLLU207 Lung cfDNA Preoperative 60 F II T2N1M0Lung Adenocarcinoma Well None 4.0 17.29 17.29 Y Y Y Cancer treatmentnaive CGPLLU208 Lung cfDNA Preoperative 56 F II T2N1M0 LungAdenocarcinoma Moderate None 3.0 24.34 24.34 Y Y Y Cancer treatmentnaive CGPLLU209 Lung cfDNA Preoperative 65 M II T2aN0M0 Lung Large CelPoor None 5.5 53.95 53.95 Y Y Y Cancer treatment naive CarcinomaCGPLLU244 Lung cfDNA Pre-treatment, 66 F IV NA Right UpperAdenocarcinoma Moderate/ Liver, Rib, 4.5 17.84 17.84 Y N Y Cancer Day −7Lobe of Lung Poor Brain, Pleura CGPLLU244 Lung cfDNA Pre-treatment, 66 FIV NA Right Upper Adenocarcinoma Moderate/ Liver, Rib, 4.5 17.84 17.84 YN Y Cancer Day −1 Lobe of Lung Poor Brain, Pleura CGPLLU244 Lung cfDNAPost-treatment, 66 F IV NA Right Upper Adenocarcinoma Moderate/ Liver,Rib, 4.5 17.84 17.84 Y N Y Cancer Day 6 Lobe of Lung Poor Brain, PleuraCGPLLU244 Lung cfDNA Post-treatment, 66 F IV NA Right UpperAdenocarcinoma Moderate/ Liver, Rib, 4.5 17.84 17.84 Y N Y Cancer Day 62Lobe of Lung Poor Brain, Pleura CGPLLU245 Lung cfDNA Pre-treatment, 49 MIV T2aN2M1B Left Upper Adenocarcinoma NA Brain 4.7 19.42 19.42 Y N YCancer Day 32 Lobe of Lung CGPLLU245 Lung cfDNA Pre-treatment, 49 M IVT2aN2M1B Left Upper Adenocarcinoma NA Brain 4.7 19.42 19.42 Y N Y CancerDay 0 Lobe of Lung CGPLLU245 Lung cfDNA Post-treatment, 49 M IV T2aN2M1BLeft Upper Adenocarcinoma NA Brain 4.7 19.42 19.42 Y N Y Cancer Day 7Lobe of Lung CGPLLU245 Lung cfDNA Post-treatment, 49 M IV T2aN2M1B LeftUpper Adenocarcinoma NA Brain 4.7 19.42 19.42 Y N Y Cancer Day 21 Lobeof Lung CGPLLU246 Lung cfDNA Pre-treatment, 65 F IV NA Right LowerAdenocarcinoma Poor Peura 5.5 18.51 18.51 Y N Y Cancer Day −21 Lobe ofLung CGPLLU246 Lung cfDNA Pre-treatment, 65 F IV NA Right LowerAdenocarcinoma Poor Peura 5.5 18.51 18.51 Y N Y Cancer Day 0 Lobe ofLung CGPLLU246 Lung cfDNA Post-treatment, 65 F IV NA Right LowerAdenocarcinoma Poor Peura 5.5 18.51 18.51 Y N Y Cancer Day 9 Lobe ofLung CGPLLU246 Lung cfDNA Post-treatment, 65 F IV NA Right LowerAdenocarcinoma Poor Peura 5.5 18.51 18.51 Y N Y Cancer Day 42 Lobe ofLung CGPLLU264 Lung cfDNA Pre-treatment, 84 M IV T4N2BM1 LeftAdenocarcinoma NA Lung 4.0 22.97 22.97 Y N Y Cancer Day −1 Middle LungCGPLLU264 Lung cfDNA Post-treatment, 84 M IV T4N2BM1 Left AdenocarcinomaNA Lung 4.5 10.53 10.53 Y N Y Cancer Day 8 Middle Lung CGPLLU264 LungcfDNA Post-treatment, 84 M IV T4N2BM1 Left Adenocarcinoma NA Lung 3.07.15 7.15 Y N Y Cancer Day 27 Middle Lung CGPLLU264 Lung cfDNAPost-treatment, 84 M IV T4N2BM1 Left Adenocarcinoma NA Lung 4.0 9.609.60 Y N Y Cancer Day 69 Middle Lung CGPLLU265 Lung cfDNA Pre-treatment,71 F IV T1N0Mx Left Lower Adenocarcinoma NA None 4.2 7.16 7.16 Y N YCancer Day 0 Lobe of Lung CGPLLU265 Lung cfDNA Post-treatment, 71 F IVT1N0Mx Left Lower Adenocarcinoma NA None 4.0 8.11 8.11 Y N Y Cancer Day3 Lobe of Lung CGPLLU265 Lung cfDNA Post-treatment, 71 F IV T1N0Mx LeftLower Adenocarcinoma NA None 4.2 7.53 7.53 Y N Y Cancer Day 7 Lobe ofLung CGPLLU265 Lung cfDNA Post-treatment, 71 F IV T1N0Mx Left LowerAdenocarcinoma NA None 5.0 16.17 16.17 Y N Y Cancer Day 84 Lobe of LungCGPLLU266 Lung cfDNA Pre-treatment, 78 M IV T2aN1 Left LowerAdenocarcinoma Moderate None 5.0 5.32 5.32 Y N Y Cancer Day 0 Lobe ofLung CGPLLU266 Lung cfDNA Post-treatment, 78 M IV T2aN1 Left LowerAdenocarcinoma Moderate None 3.5 6.31 6.31 Y N Y Cancer Day 16 Lobe ofLung CGPLLU266 Lung cfDNA Post-treatment, 78 M IV T2aN1 Left LowerAdenocarcinoma Moderate None 5.0 7.64 7.64 Y N Y Cancer Day 83 Lobe ofLung CGPLLU266 Lung cfDNA Post-treatment, 78 M IV T2aN1 Left LowerAdenocarcinoma Moderate None 5.0 14.39 14.39 Y N Y Cancer Day 328 Lobeof Lung CGPLLU267 Lung cfDNA Pre-treatment, 55 F IV T3NxM1a Right UpperSquamous Cel Poor Lung 4.5 2.87 2.87 Y N Y Cancer Day −1 Lobe of LungCarcinoma CGPLLU267 Lung cfDNA Post-treatment, 55 F IV T3NxM1a RightUpper Squamous Cel Poor Lung 4.5 3.34 3.34 Y N Y Cancer Day 34 Lobe ofLung Carcinoma CGPLLU267 Lung cfDNA Post-treatment, 55 F IV T3NxM1aRight Upper Squamous Cel Poor Lung 3.5 3.00 3.00 Y N Y Cancer Day 90Lobe of Lung Carcinoma CGPLLU269 Lung cfDNA Pre-treatment, 52 F IVT1CNxM1C Right Adenocarcinoma NA Brain, Liver, 5.0 11.40 11.40 Y N YCancer Day 0 Paratracheal Bone, Peura Lesion CGPLLU269 Lung cfDNAPost-treatment, 52 F IV T1CNxM1C Right Adenocarcinoma NA Brain, Liver,5.0 8.35 8.35 Y N Y Cancer Day 9 Paratracheal Bone, Peura LesionCGPLLU269 Lung cfDNA Post-treatment, 52 F IV T1CNxM1C RightAdenocarcinoma NA Brain, Liver, 3.5 17.79 17.79 Y N Y Cancer Day 28Paratracheal Bone, Peura Lesion CGPLLU271 Lung cfDNA Post-treatment, 73M IV T1aNxM1 Left Upper Adenocarcinoma Moderate Peura 4.0 4.70 4.70 Y NY Cancer Day 259 Lobe of Lung CGPLLU271 Lung cfDNA Pre-treatment, 73 MIV T1aNxM1 Left Upper Adenocarcinoma Moderate Peura 5.0 18.86 18.86 Y NY Cancer Day 0 Lobe of Lung CGPLLU271 Lung cfDNA Post-treatment, 73 M IVT1aNxM1 Left Upper Adenocarcinoma Moderate Peura 4.5 13.84 13.84 Y N YCancer Day 8 Lobe of Lung CGPLLU271 Lung cfDNA Post-treatment, 73 M IVT1aNxM1 Left Upper Adenocarcinoma Moderate Peura 3.5 13.46 13.46 Y N YCancer Day 20 Lobe of Lung CGPLLU271 Lung cfDNA Post-treatment, 73 M IVT1aNxM1 Left Upper Adenocarcinoma Moderate Peura 4.0 13.77 13.77 Y N YCancer Day 104 Lobe of Lung CGPLLU43 Lung cfDNA Pre-treatment, 57 F IVT1BN0M0 Right Lower Adenocarcinoma Moderate None 4.9 2.17 2.17 Y N YCancer Day −1 Lobe of Lung CGPLLU43 Lung cfDNA Post-treatment, 57 F IVT1BN0M0 Right Lower Adenocarcinoma Moderate None 3.7 3.26 3.26 Y N YCancer Day 6 Lobe of Lung CGPLLU43 Lung cfDNA Post-treatment, 57 F IVT1BN0M0 Right Lower Adenocarcinoma Moderate None 4.0 4.12 4.12 Y N YCancer Day 27 Lobe of Lung CGPLLU43 Lung cfDNA Post-treatment, 57 F IVT1BN0M0 Right Lower Adenocarcinoma Moderate None 3.7 8.20 8.20 Y N YCancer Day 83 Lobe of Lung CGPLLU86 Lung cfDNA Pre-treatment, 55 M IV NALeft Upper Adenocarcinoma NA Lung 4.0 7.90 7.90 Y N Y Cancer Day 0 Lobeof Lung CGPLLU86 Lung cfDNA Post-treatment, 55 M IV NA Left UpperAdenocarcinoma NA Lung 4.0 7.90 7.90 Y N Y Cancer Day 0.5 Lobe of LungCGPLLU86 Lung cfDNA Post-treatment, 55 M IV NA Left Upper AdenocarcinomaNA Lung 4.0 7.90 7.90 Y N Y Cancer Day 7 Lobe of Lung CGPLLU86 LungcfDNA Post-treatment, 55 M IV NA Left Upper Adenocarcinoma NA Lung 4.07.90 7.90 Y N Y Cancer Day 17 Lobe of Lung CGPLLU88 Lung cfDNAPre-treatment, 59 M IV NA Right Adenocarcinoma NA None 5.0 27.66 27.66 YN Y Cancer Day 0 Middle Lobe of Lung CGPLLU88 Lung cfDNA Post-treatment,59 M IV NA Right Adenocarcinoma NA None 5.0 6.49 6.49 Y N Y Cancer Day 7Middle Lobe of Lung CGPLLU88 Lung cfDNA Post-treatment, 59 M IV NA RightAdenocarcinoma NA None 4.0 3.04 3.04 Y N Y Cancer Day 297 Middle Lobe ofLung CGPLLU89 Lung cfDNA Pre-treatment, 54 F IV NA Right UpperAdenocarcinoma NA Brain, 8.0 8.43 8.43 Y N Y Cancer Day 0 Lobe of LungBone, Lung CGPLLU89 Lung cfDNA Post-treatment, 54 F IV NA Right UpperAdenocarcinoma NA Brain, 8.0 8.43 8.43 Y N Y Cancer Day 7 Lobe of LungBone, Lung CGPLLU89 Lung cfDNA Post-treatment, 54 F IV NA Right UpperAdenocarcinoma NA Brain, 8.0 8.43 8.43 Y N Y Cancer Day 22 Lobe of LungBone, Lung CGPLOV11 Ovarian cfDNA Preoperative 51 F IV T3cN0M1 RightEndometrioid Moderate Omentum 3.4 17.35 17.35 Y Y Y Cancer treatmentnaive Ovary Adenocarcinoma CGPLOV12 Ovarian cfDNA Preoperative 45 F IT1aN0MX Ovary Endometrioid NA None 3.2 12.44 12.44 Y N Y Cancertreatment naive Adenocarcinoma CGPLOV13 Ovarian cfDNA Preoperative 62 FIV T1bN0M1 Right Endometrioid Poor Omentum 3.8 27.00 27.00 Y Y Y Cancertreatment naive Ovary Adenocarcinoma CGPLOV15 Ovarian cfDNA Preoperative54 F III T3N1M0 Ovary Adenocarcinoma Poor None 5.0 4.77 4.77 Y Y YCancer treatment naive CGPLOV16 Ovarian cfDNA Preoperative 40 F IIIT3aN0M0 Ovary Serous Moderate None 4.5 27.28 27.28 Y N Y Cancertreatment naive Adenocarcinoma CGPLOV19 Ovarian cfDNA Preoperative 52 FII T2aN0M0 Ovary Endometrioid Moderate None 5.0 23.46 23.46 Y Y Y Cancertreatment naive Adenocarcinoma CGPLOV20 Ovarian cfDNA Preoperative 52 FII T2aN0M0 Left Endometrioid Poor None 4.2 5.67 5.67 Y Y Y Cancertreatment naive Ovary Adenocarcinoma CGPLOV21 Ovarian cfDNA Preoperative51 F IV TanyN1M1 Ovary Serous Poor Omentum, 4.3 56.32 56.32 Y Y Y Cancertreatment naive Adenocarcinoma Appendix CGPLOV22 Ovarian cfDNAPreoperative 64 F III T1cNXMX Left Serous Well None 4.6 17.42 17.42 Y YY Cancer treatment naive Ovary Adenocarcinoma CGPLOV23 Ovarian cfDNAPreoperative 47 F I T1aN0M0 Ovary Serous Poor None 5.0 26.73 26.73 Y N YCancer treatment naive Adenocarcinoma CGPLOV24 Ovarian cfDNAPreoperative 14 F I T1aN0M0 Ovary Germ Cell Poor None 4.2 10.71 10.71 YN Y Cancer treatment naive Tumor CGPLOV25 Ovarian cfDNA Preoperative 18F I T1aN0M0 Ovary Germ Cell Poor None 4.8 6.78 6.78 Y N Y Cancertreatment naive Tumor CGPLOV26 Ovarian cfDNA Preoperative 35 F I T1aN0M0Ovary Germ Cell Poor None 4.5 27.90 27.90 Y N Y Cancer treatment naiveTumor CGPLOV28 Ovarian cfDNA Preoperative 63 F I T1aN0M0 Right Serous NANone 3.2 10.74 10.74 Y N Y Cancer treatment naive Ovary CarcinomaCGPLOV31 Ovarian cfDNA Preoperative 45 F III T3aNxM0 Right Clear Cell NANone 4.0 14.45 14.45 Y N Y Cancer treatment naive Ovary adenocarcinomaCGPLOV32 Ovarian cfDNA Preoperative 53 F I T1aNxM0 Left Mucinous NA None3.2 27.36 27.36 Y N Y Cancer treatment naive Ovary Cystadenoma CGPLOV37Ovarian cfDNA Preoperative 40 F I T1cN0M0 Ovary Serous NA None 3.2 46.8846.88 Y N Y Cancer treatment naive Carcinoma CGPLOV38 Ovarian cfDNAPreoperative 46 F I T1cN0M0 Ovary Serous NA None 2.4 34.29 34.29 Y N YCancer treatment naive Carcinoma CGPLOV40 Ovarian cfDNA Preoperative 53F IV T3N0M1 Ovary Serous NA Omentum, 1.6 193.60 156.25 Y N Y Cancertreatment naive Carcinoma Uterus, Appendix CGPLOV41 Ovarian cfDNAPreoperative 57 F IV T3N0M1 Ovary Serous NA Omentum, 4.4 10.03 10.03 Y NY Cancer treatment naive Carcinoma Uterus, Cervix CGPLOV42 Ovarian cfDNAPreoperative 52 F I T3aN0M0 Ovary Serous NA None 4.2 49.51 49.51 Y N YCancer treatment naive Carcinoma CGPLOV43 Ovarian cfDNA Preoperative 30F I T1aN0M0 Ovary Mucinous NA None 4.4 9.09 9.09 Y N Y Cancer treatmentnaive Cyst- adenocarcinoma CGPLOV44 Ovarian cfDNA Preoperative 69 F IT1aN0M0 Ovary Mucinous NA None 4.5 8.79 8.79 Y N Y Cancer treatmentnaive Adenocarcinoma CGPLOV46 Ovarian cfDNA Preoperative 58 F I T1bN0M0Ovary Serous NA None 4.1 8.97 8.97 Y N Y Cancer treatment naiveCarcinoma CGPLOV47 Ovarian cfDNA Preoperative 41 F I T1aN0M0 OvarySerous NA None 4.5 19.35 19.35 Y N Y Cancer treatment naiveAdenocarcinoma CGPLOV48 Ovarian cfDNA Preoperative 52 F I T1bN0M0 OvarySerous NA None 3.5 22.80 22.80 Y N Y Cancer treatment naive CarcinomaCGPLOV49 Ovarian cfDNA Preoperative 68 F III T3bN0M0 Ovary Serous NANone 4.2 16.48 16.48 Y N Y Cancer treatment naive Carcinoma CGPLOV50Ovarian cfDNA Preoperative 30 F III T3cN0M0 Ovary Serous NA None 4.58.89 8.89 Y N Y Cancer treatment naive Carcinoma CGPLPA112 PancreaticcfDNA Preoperative 58 M II NA Intra NA NA None 3.5 18.52 18.52 Y N NCancer treatment naive Pancreatic Bile Duct CGPLPA113 Duodenal cfDNAPreoperative 71 M I NA Intra NA NA None 4.8 8.24 8.24 Y N N Cancertreatment naive Pancreatic Bile Duct CGPLPA114 Bile Duct cfDNAPreoperative NA F II NA Intra NA NA None 4.8 26.43 26.43 Y N N Cancertreatment naive Pancreatic Bile Duct CGPLPA115 Bile Duct cfDNAPreoperative NA M IV NA Intra NA NA NA 5.0 31.41 31.41 Y N N Cancertreatment naive Hepatic Bile Duct CGPLPA117 Bile Duct cfDNA PreoperativeNA M II NA Intra NA NA NA 3.4 2.29 2.29 Y N N Cancer treatment naivePancreatic Bile Duct CGPLPA118 Bile Duct cfDNA Preoperative 68 F I NABile Duct Intra- NA None 3.8 9.93 9.93 Y N Y Cancer treatment naiveAmpuliary Bile Duct CGPLPA122 Bile Duct cfDNA Preoperative 62 F II NABile Duct Intra- NA None 3.8 66.54 32.89 Y N Y Cancer treatment naivePancreatic Bile Duct CGPLPA124 Bile Duct cfDNA Preoperative 83 F II NABile Duct Intra- moderate None 4.6 29.24 27.17 Y N Y Cancer treatmentnaive Ampuliary Bile Duct CGPLPA125 Bile Duct cfDNA Preoperative 58 M IINA Bile Duct Intra- poor None 2.7 8.31 8.31 Y N N Cancer treatment naivePancreatic Bile Duct CGPLPA126 Bile Duct cfDNA Preoperative 60 M II NABile Duct Intra- NA None 4.2 80.56 29.07 Y N Y Cancer treatment naivePancreatic Bile Duct CGPLPA127 Bile Duct cfDNA Preoperative 71 F IV NABile Duct Extra- NA NA 3.0 20.60 20.60 Y N N Cancer treatment naivePancreatic Bile Duct CGPLPA128 Bile Duct cfDNA Preoperative 67 M II NABile Duct Intra- NA None 3.9 5.91 5.91 Y N Y Cancer treatment naivePancreatic Bile Duct CGPLPA129 Bile Duct cfDNA Preoperative 56 F II NABile Duct Intra- NA None 4.6 27.07 27.07 Y N Y Cancer treatment naivePancreatic Bile Duct CGPLPA130 Bile Duct cfDNA Preoperative 82 F II NABile Duct Intra- well None 4.0 4.34 4.34 Y N Y Cancer treatment naiveAmpuliary Bile Duct CGPLPA131 Bile Duct cfDNA Preoperative 71 M II NABile Duct Intra- NA None 3.9 68.95 32.05 Y N Y Cancer treatment naivePancreatic Bile Duct CGPLPA134 Bile Duct cfDNA Preoperative 68 M II NABile Duct Intra- NA None 4.1 58.98 30.49 Y N Y Cancer treatment naivePancreatic Bile Duct CGPLPA135 Bile Duct cfDNA Preoperative 67 F I NABile Duct Intra- NA NA 3.9 4.22 4.22 Y N N Cancer treatment naivePancreatic Bile Duct CGPLPA136 Bile Duct cfDNA Preoperative 69 F II NABile Duct Intra- NA None 4.1 20.23 20.23 Y N Y Cancer treatment naivePancreatic Bile Duct CGPLPA137 Bile Duct cfDNA Preoperative NA M II NABile Duct NA NA NA 4.0 5.75 5.75 Y N N Cancer treatment naive CGPLPA139Bile Duct cfDNA Preoperative NA M IV NA Bile Duct NA NA NA 4.0 14.8914.89 Y N N Cancer treatment naive CGPLPA14 Pancreatic cfDNAPreoperative 68 M II NA Pancreas Ductal Poor None 4.0 1.30 1.30 Y N NCancer treatment naive Adenocarcinoma CGPLPA140 Bile Duct cfDNAPreoperative 52 M II NA Extra- Intra- Poor None 4.7 29.34 26.60 Y N YCancer treatment naive Hepatic Pancreatic Bile Duct Bile Duct CGPLPA141Bile Duct cfDNA Preoperative 68 F II NA Extra- Intra- Moderate None 2.853.67 44.64 Y N N Cancer treatment naive Hepatic Pancreatic Bile DuctBile Duct CGPLPA15 Pancreatic cfDNA Preoperative 70 F II NA PancreasDuctal Well Lymph 4.0 1.92 1.92 Y N N Cancer treatment naiveAdenocarcinoma Node CGPLPA155 Bile Duct cfDNA Preoperative NA F II NA NANA NA NA 4.0 25.72 25.72 Y N N Cancer treatment naive CGPLPA156Pancreatic cfDNA Preoperative 73 F II NA Pancreas Ductal Poor Lymph 4.57.54 7.54 Y N N Cancer treatment naive Adenocarcinoma Node CGPLPA165Bile Duct cfDNA Preoperative 42 M I NA Bile Duct Intra- well None 3.910.48 10.48 Y N N Cancer treatment naive Pancreatic Bile Duct withMeduliary Features CGPLPA168 Bile Duct cfDNA Preoperative 58 M II NABile Duct NA NA NA 3.0 139.12 34.72 Y N N Cancer treatment naiveCGPLPA17 Pancreatic cfDNA Preoperative 65 M II NA Pancreas Ductal WellLymph 4.0 13.08 13.08 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA184 Bile Duct cfDNA Preoperative 75 F II NA Bile Duct Intra- NANone NA NA NA Y N N Cancer treatment naive Pancreatic Bile DuctCGPLPA187 Bile Duct cfDNA Preoperative 67 F II NA Bile Duct Intra- NANone NA NA NA Y N N Cancer treatment naive Pancreatic Bile Duct CGPLPA23Pancreatic cfDNA Preoperative 58 F II NA Pancreas Ductal Moderate Lymph4.0 16.62 16.62 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA25 Pancreatic cfDNA Preoperative 69 F II NA Pancreas Ductal PoorLymph 4.0 8.71 8.71 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA26 Pancreatic cfDNA Preoperative 64 M II NA Pancreas Ductal WellLymph 4.0 6.97 6.97 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA28 Pancreatic cfDNA Preoperative 79 F II NA Pancreas Ductal WellLymph 4.0 18.13 18.13 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA33 Pancreatic cfDNA Preoperative 67 F II NA Pancreas Ductal WellLymph 4.0 1.80 1.80 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA34 Pancreatic cfDNA Preoperative 73 M II NA Pancreas Ductal WellLymph 4.0 3.36 3.36 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA37 Pancreatic cfDNA Preoperative 67 F II NA Pancreas Ductal NALymph 4.0 21.83 21.83 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA38 Pancreatic cfDNA Preoperative 65 M II NA Pancreas DuctalModerate None 4.0 5.29 5.29 Y N N Cancer treatment naive AdenocarcinomaCGPLPA39 Pancreatic cfDNA Preoperative 67 F II NA Pancreas Ductal WellLymph 4.0 11.73 11.73 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA40 Pancreatic cfDNA Preoperative 64 M II NA Pancreas Ductal WellLymph 4.0 4.78 4.78 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA42 Pancreatic cfDNA Preoperative 73 M II NA Pancreas DuctalModerate Lymph 4.0 3.41 3.41 Y N N Cancer treatment naive AdenocarcinomaNode CGPLPA46 Pancreatic cfDNA Preoperative 59 F II NA Pancreas DuctalPoor Lymph 4.0 0.74 0.74 Y N N Cancer treatment naive AdenocarcinomaNode CGPLPA47 Pancreatic cfDNA Preoperative 67 M II NA Pancreas DuctalWell Lymph 4.0 6.01 6.01 Y N N Cancer treatment naive AdenocarcinomaNode CGPLPA48 Pancreatic cfDNA Preoperative 72 F II NA Pancreas DuctalWell None NA NA NA Y N N Cancer treatment naive Adenocarcinoma CGPLPA52Pancreatic cfDNA Preoperative 63 M II NA Pancreas Ductal Moderate None2.5 9.86 9.86 Y N N Cancer treatment naive Adenocarcinoma CGPLPA53Pancreatic cfDNA Preoperative 46 M I NA Pancreas Ductal Poor Lymph 3.014.48 14.48 Y N N Cancer treatment naive Adenocarcinoma Node CGPLPA58Pancreatic cfDNA Preoperative 74 F II NA Pancreas Ductal NA None 3.06.87 6.87 Y N N Cancer treatment naive Adenocarcinoma CGPLPA59Pancreatic cfDNA Preoperative 59 F II NA Pancreas Ductal Well Lymph NANA NA Y N N Cancer treatment naive Adenocarcinoma Node or AdenomaCGPLPA67 Pancreatic cfDNA Preoperative 55 M III NA Pancreas Ductal WellLymph 3.2 9.72 9.72 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA69 Pancreatic cfDNA Preoperative 70 M I NA Pancreas Ductal WellNone 2.0 1.72 1.72 Y N N Cancer treatment naive Adenocarcinoma CGPLPA71Pancreatic cfDNA Preoperative 64 M II NA Pancreas Ductal Well Lymph 2.239.07 39.07 Y N N Cancer treatment naive Adenocarcinoma Node CGPLPA74Pancreatic cfDNA Preoperative 71 F II NA Pancreas Ductal Moderate Lymph2.5 4.99 4.99 Y N N Cancer treatment naive Adenocarcinoma Node CGPLPA76Pancreatic cfDNA Preoperative 69 M II NA Pancreas Ductal Poor None 2.523.19 23.19 Y N N Cancer treatment naive Adenocarcinoma CGPLPA85Pancreatic cfDNA Preoperative 77 F II NA Pancreas Ductal Poor Lymph 3.0152.46 41.67 Y N N Cancer treatment naive Adenocarcinoma Node CGPLPA86Pancreatic cfDNA Preoperative 66 M II NA Pancreas Ductal Moderate Lymph2.5 11.92 11.92 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA92 Pancreatic cfDNA Preoperative 72 M II NA Pancreas Ductal NALymph 2.0 5.34 5.34 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA93 Pancreatic cfDNA Preoperative 48 M II NA Pancreas Ductal PoorNone 3.0 96.28 41.67 Y N N Cancer treatment naive AdenocarcinomaCGPLPA94 Pancreatic cfDNA Preoperative 72 F II NA Pancreas Ductal NALymph 3.0 29.66 29.66 Y N N Cancer treatment naive Adenocarcinoma NodeCGPLPA95 Pancreatic cfDNA Preoperative 64 F II NA Pancreas Ductal WellLymph NA NA NA Y N N Cancer treatment naive Adenocarcinoma Node CGST102Gastric cfDNA Preoperative 76 F II T3N0M0 Stomach Tubular Moderate None4.1 8.03 8.03 Y N Y Cancer treatment naive Adenocarcinoma CGST11 GastriccfDNA Preoperative 49 M IV TXNXM1 Stomach Mixed Moderate None 3.8 3.573.57 Y N N Cancer treatment naive Carcinoma CGST110 Gastric cfDNAPreoperative 77 M III T4AN3aM0 Stomach Tubular Moderate None 3.8 5.005.00 Y N Y Cancer treatment naive Adenocarcinoma CGST114 Gastric cfDNAPreoperative 65 M III T4N1M0 Stomach Tubular Poor None 4.4 10.35 10.35 YN Y Cancer treatment naive Adenocarcinoma CGST13 Gastric cfDNAPreoperative 72 F II T1AN2M0 Stomach Signet Ring Poor None 4.4 24.3324.33 Y N Y Cancer treatment naive Cell Carcinoma CGST131 Gastric cfDNAPreoperative 63 M III T2N3aM0 Stomach Signet ring Poor None 4.0 4.284.28 Y N N Cancer treatment naive cell Carcinoma CGST141 Gastric cfDNAPreoperative 33 F III T3N2M0 Stomach Signet Ring Poor None 4.4 10.8410.84 Y N Y Cancer treatment naive Cell Carcinoma CGST16 Gastric cfDNAPreoperative 78 M III T4AN3aM0 Stomach Tubular Poor None 4.0 40.69 40.69Y N Y Cancer treatment naive Adenocarcinoma CGST18 Gastric cfDNAPreoperative 50 M II T3N0M0 Stomach Mucinous Well None 4.3 9.78 9.78 Y NY Cancer treatment naive Adenocarcinoma CGST21 Gastric cfDNAPreoperative 39 M II T2N1(mi)M0 Stomach Papillary Moderate None 4.0 0.830.83 Y N N Cancer treatment naive Adenocarcinoma CGST26 Gastric cfDNAPreoperative 51 M IV TXNXM1 Stomach Signet ring Poor None 3.5 5.56 5.56Y N N Cancer treatment naive cell Carcinoma CGST28 Gastric cfDNAPreoperative 55 M X TXNXMX Stomach Undifferentiated Poor None 4.0 5.865.86 Y N Y Cancer treatment naive Carcinoma CGST30 Gastric cfDNAPreoperative 64 F III T3N2M0 Stomach Signet Ring Poor None 3.0 4.22 4.22Y N Y Cancer treatment naive Cell Carcinoma CGST32 Gastric cfDNAPreoperative 67 M II T3N1M0 Stomach Tubular Moderate None 4.0 11.4911.49 Y N Y Cancer treatment naive Adenocarcinoma CGST33 Gastric cfDNAPreoperative 61 M I T2N0M0 Stomach Tubular Moderate None 3.5 5.71 5.71 YN Y Cancer treatment naive Adenocarcinoma CGST38 Gastric cfDNAPreoperative 71 F 0 T0N0M0 Stomach Mucinous NA None 4.0 NA NA Y N NCancer treatment naive Adenocarcinoma CGST39 Gastric cfDNA Preoperative51 M IV TXNXM1 Stomach Signet Ring Poor None 3.5 20.69 20.69 Y N YCancer treatment naive Cell Carcinoma CGST41 Gastric cfDNA Preoperative66 F IV TXNXM1 Stomach Signet Ring Poor None 3.5 7.83 7.83 Y N Y Cancertreatment naive Cell Carcinoma CGST45 Gastric cfDNA Preoperative 41 F IIT3N0M0 Stomach Signet Ring Poor None 3.8 7.14 7.14 Y N Y Cancertreatment naive Cell Carcinoma CGST47 Gastric cfDNA Preoperative 74 F IT1AN0M0 Stomach Tubular Moderate None 4.0 4.55 4.55 Y N Y Cancertreatment naive Adenocarcinoma CGST48 Gastric cfDNA Preoperative 62 M IVTXNXM1 Stomach Tubular Poor None 4.5 8.79 8.79 Y N Y Cancer treatmentnaive Adenocarcinoma CGST53 Gastric cfDNA Preoperative 70 M 0 T0N0M0Stomach NA NA None 3.8 15.82 15.82 Y N N Cancer treatment naive CGST58Gastric cfDNA Preoperative 58 M III T4AN3bM0 Stomach Signet Ring PoorNone 3.8 19.81 19.81 Y N Y Cancer treatment naive Cell Carcinoma CGST67Gastric cfDNA Preoperative 69 M I T1RN0M0 Stomach Tubular Moderate None3.0 23.01 23.01 Y N N Cancer treatment naive adenocarcinoma CGST77Gastric cfDNA Preoperative 70 M IV TXNXM1 Stomach Tubular Moderate None4.5 15.09 15.09 Y N N Cancer treatment naive adenocarcinoma CGST80Gastric cfDNA Preoperative 58 M III T3N3aM0 Stomach Mucinous Poor None4.5 8.56 8.56 Y N Y Cancer treatment naive Adenocarcinoma CGST81 GastriccfDNA Preoperative 64 F I T2N0M1 Stomach Signet Ring Poor None 3.5 37.3237.32 Y N Y Cancer treatment naive Cell Carcinoma CGH14 Healthy Human NANA M NA NA NA NA NA NA NA NA NA Y N N Adult elutriated lymphoc CGH15Healthy Human NA NA F NA NA NA NA NA NA NA NA NA Y N N Adult elutriatedlymphoc *NA denotes data not available or not applicable for healthyindividuals.

APPENDIX B Table 2 Summary of targeted cfDNA analyses Fragment ProfileMutation Bases in Bases Mapped to Bases Mapped to Percent Mapped toTotal Distinct Patient Patient Type Timepoint Analysis Analysis ReadLength Target Region Genome Target Regions Target Regions CoverageCoverage CGCRC291 Colorectal Cancer Preoperative, Treatment naïve Y Y100 80930 7501485600 3771359756 50% 44345 10359 CGCRC292 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 6736035200 309888697346% 36448 8603 CGCRC293 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 6300244000 2818734206 45% 33117 5953 CGCRC294 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 7766872600 391179670950% 46016 12071 CGCRC295 Colorectal Cancer Preoperative, Treatment naïveY N 100 80930 8240660200 3478059753 42% 40787 5826 CGCRC296 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 5718556500 289854935651% 33912 10180 CGCRC291 Colorectal Cancer Preoperative, Treatment naïveY N 100 80930 7550826100 3717222432 49% 43545 5870 CGCRC298 ColorectalCancer Preoperative, Treatment naïve Y N 100 80930 125010364006096393764 49% 71196 9617 CGCRC299 Colorectal Cancer Preoperative,Treatment naïve Y Y 100 80930 7812602900 4121569690 53% 48098 10338CGCRC300 Colorectal Cancer Preoperative, Treatment naïve Y Y 100 809308648090300 3962285136 46% 46364 5756 CGCRC301 Colorectal CancerPreoperative, Treatment naïve Y Y 100 80930 7538758100 3695480348 49%43024 6618 CGCRC302 Colorectal Cancer Preoperative, Treatment naïve Y Y100 80930 8573658300 4349420574 51% 51006 13799 CGCRC303 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 5224046400 250571434348% 29365 8372 CGCRC304 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 5762112600 2942170530 51% 34462 10208 CGCRC305 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 7213384100 372695348052% 43516 8589 CGCRC306 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 7075579700 3552441899 50% 41507 7372 CGCRC307 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 7572687100 349219151946% 40793 9680 CGCRC308 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 7945738000 3895908986 49% 45224 11809 CGCRC309 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 8487455800 392107981146% 45736 10739 CGCRC310 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 9003580500 4678812441 52% 54713 11139 CGCRC311 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 6528162700 327665386450% 38324 6044 CGCRC312 Colorectal Cancer Preoperative, Treatment naïveY N 100 80930 7683294300 3316719187 43% 38652 4622 CGCRC313 ColorectalCancer Preoperative, Treatment naïve Y N 100 80930 5874099200 289614872249% 33821 6506 CGCRC314 Colorectal Cancer Preoperative, Treatment naïveY N 100 80930 6883148500 3382767492 49% 39414 6664 CGCRC315 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 7497252500 377555605150% 44034 8666 CGCRC316 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 10684720400 5533857153 52% 64693 14289 CGCRC317 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 7086877600 366943421652% 43538 10944 CGCRC318 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 6880041100 3326357413 48% 39077 11571 CGCRC319 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 7485342900 398267748353% 47327 10502 CGCRC320 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 7058703200 3450648135 49% 40888 10198 CGCRC321 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 7203625900 363339689250% 43065 6499 CGCRC332 Colorectal Cancer Preoperative, Treatment naïveY N 100 80930 7202969100 3758323705 52% 44580 3243 CGCRC333 ColorectalCancer Preoperative, Treatment naïve Y Y 100 80930 8767144700 419912682748% 49781 8336 CGCRC334 Colorectal Cancer Preoperative, Treatment naïveY N 100 80930 7771869100 3944518280 51% 46518 5014 CGCRC335 ColorectalCancer Preoperative, Treatment naïve Y N 100 80930 7972524600 406490120151% 48308 6151 CGCRC336 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 8597346400 4333410573 50% 51390 7551 CGCRC337 ColorectalCancer Preoperative, Treatment naïve Y N 100 80930 7399611700 380066619951% 45083 8092 CGCRC338 Colorectal Cancer Preoperative, Treatment naïveY Y 100 80930 8029493700 4179383804 52% 49380 5831 CGCRC339 ColorectalCancer Preoperative, Treatment naïve Y N 100 80930 7938963500 409555511052% 48397 3808 CGCRC340 Colorectal Cancer Preoperative, Treatment naïveY N 100 80930 7214889500 3706643098 51% 43805 3014 CGCRC341 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 8803159200 366820852742% 43106 11957 CGCRC342 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 8478811500 3425540889 40% 40328 9592 CGCRC344 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6942167800 309823273745% 36823 2300 CGCRC345 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 8182868200 2383173431 29% 28233 7973 CGCRC346 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 7448272300 392505634153% 46679 5582 CGCRC347 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 5804744500 2986809912 51% 35490 4141 CGCRC349 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6943451600 353314527551% 41908 5762 CGCRC350 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 7434818400 3848923016 52% 45678 4652 CGCRC351 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 7306546400 363691040950% 43162 5205 CGCRC352 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 7864655000 3336939252 42% 39587 4502 CGCRC353 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 7501674800 364291937549% 43379 4666 CGCRC354 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 7938270200 2379068977 30% 28256 4858 CGCRC356 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6013175900 304675499451% 36127 3425 CGCRC357 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 6013454600 3022035300 50% 35813 4259 CGCRC358 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 7227212400 318872330344% 37992 5286 CGCRC359 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 7818567700 425110101 5% 5040 2566 CGCRC367 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6582043200 336306359751% 39844 5839 CGCRC368 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 8042242400 4101646000 51% 48636 11471 CGCRC370 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6940330100 319895412146% 38153 4826 CGCRC373 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 6587201700 3120088035 47% 37234 5190 CGCRC376 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6727983100 316241680747% 37735 3445 CGCRC377 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 6716339200 3131415570 47% 37160 4524 CGCRC378 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6523969900 241109672037% 28728 3239 CGCRC379 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 6996252100 3371081103 48% 39999 2891 CGCRC380 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 7097496300 271024444638% 32020 3251 CGCRC381 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 6961936100 3287050681 47% 38749 9357 CGCRC382 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6959048700 255232585937% 30040 5148 CGCRC384 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 7012798900 3293884583 47% 39158 3653 CGCRC385 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 7542017900 335657050545% 39884 3686 CGCRC386 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 6876059600 3064412286 45% 36431 2787 CGCRC387 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 7399564700 304725456041% 36141 6675 CGCRC386 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 6592692900 3137284885 48% 37285 5114 CGCRC389 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6651206300 310210094147% 36764 6123 CGCRC390 Colorectal Cancer Preoperative, Treatment naïveN Y 100 80930 7260616800 3376667585 47% 40048 4368 CGCRC391 ColorectalCancer Preoperative, Treatment naïve N Y 100 80930 6883624500 320287788147% 37978 5029 CGLU316 Lung Cancer Pre-treatment Day −53 Y N 100 809307864415100 1991331171 25% 23601 3565 CGLU316 Lung Cancer Pre-treatment,Day −53 Y N 100 80930 7502591600 3730963390 50% 44262 3966 CGLU316 LungCancer Pro-treatment, Day −53 Y N 100 80930 6582515900 3187059470 48%37813 3539 CGLU316 Lung Cancer Pre-treatment, Day −53 Y N 100 609306587281800 1947630979 30% 23094 4439 CGLU344 Lung Cancer Pretreatment,Day −21 Y N 100 80930 6151628500 2748983603 45% 32462 8063 CGLU344 LungCancer Pre-treatment, Day −21 Y N 100 80930 7842910900 1147703178 15%13565 4303 CGLU344 Lung Cancer Pretreatment, Day −21 Y N 100 809305838083100 2291108925 39% 27067 4287 CGLU344 Lung Cancer Pre-treatment,Day −21 Y N 100 80930 7685989200 3722274529 48% 43945 3471 CGLU369 LungCancer Pre-treatment, Day −2 Y N 100 80930 7080245300 1271457982 18%15109 2354 CGLU369 Lung Cancer Pre-treatment, Day −2 Y N 100 009307078131900 1482448715 21% 17583 4275 CGLU369 Lung Cancer Pre-treatment,Day −2 Y N 100 60930 6904701700 2124660124 31% 25230 5278 CGLU369 LungCancer Pre-treatment, Day −2 Y N 100 80930 7003452200 3162195578 45%37509 6062 CGLU373 Lung Cancer Pro-treatment, Day −2 Y N 100 009306346267200 3053520676 48% 36137 6251 CGLU373 Lung Cancer Pre-treatment,Day −2 Y N 100 80930 6517189900 3192984468 49% 38066 8040 CGLU373 LungCancer Pre-treatment, Day −2 Y N 100 60930 7767146300 3572598842 46%42378 5306 CGLU373 Lung Cancer Pre-treatment, Day −2 Y N 100 809307190999100 3273648804 46% 38784 4454 CGPLBR100 Breast CancerPreoperative, Treatment naïve N Y 100 00930 7299964400 3750278051 51%44794 3249 CGPLBR101 Breast Cancer Preoperative, Treatment naïve N Y 10080930 7420822800 3810365416 51% 45565 9784 CGPLBR102 Breast CancerPreoperative, Treatment naïve N Y 100 80930 6679304900 3269688319 49%38679 7613 CGPLBR103 Breast Cancer Preoperative, Treatment naïve N Y 10060930 7040304400 3495542468 50% 41786 6748 CGPLBR104 Breast CancerPreoperative, Treatment naïve N Y 100 80930 7188389200 3716096781 52%44316 9448 CGPLBR38 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 7810293900 4057576306 52% 48098 9868 CGPLBR39 Breast CancerPreoperative, Treatment naïve N Y 100 80930 7745701500 3805623239 49%45084 11065 CGPLBR40 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 7558990500 3652442341 48% 43333 12948 CGPLBR41 Breast CancerPreoperative, Treatment naïve N Y 100 80930 7900994600 3836800101 49%45535 10847 CGPLBR44 Breast Cancer Preoperative, Treatment naïve Y N 10080930 7017744200 3269110569 47% 38672 8344 CGPLBR48 Breast CancerPreoperative, Treatment naïve Y Y 100 80930 5629044200 2611554623 46%30860 8652 CGPLBR49 Breast Cancer Preoperative, Treatment naïve N Y 10080930 5784711600 2673457893 46% 31274 10429 CGPLBR55 Breast CancerPreoperative, Treatment naïve Y Y 100 80930 8309154900 4306956261 52%51143 8328 CGPLBR57 Breast Cancer Preoperative, Treatment naïve N Y 10080930 8636181000 4391502618 51% 52108 5857 CGPLBR59 Breast CancerPreoperative, Treatment naïve N Y 100 80930 8799457700 4152328555 47%49281 5855 CGPLBR61 Breast Cancer Preoperative, Treatment naïve N Y 10080930 8163706700 3952010628 48% 46755 8522 CGPLBR63 Breast CancerPreoperative, Treatment naïve Y Y 100 80930 7020533100 3542447304 50%41956 4773 CGPLBR67 Breast Cancer Preoperative, Treatment naïve Y N 10080930 8264353900 3686093696 45% 43516 7752 CGPLBR68 Breast CancerPreoperative, Treatment naïve N Y 100 80930 7629312300 4078969547 53%48389 7402 CGPLBR69 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 7571501500 3857354512 51% 45322 7047 CGPLBR70 Breast CancerPreoperative, Treatment naïve Y Y 100 80930 7251760700 3641333708 50%43203 8884 CGPLBR71 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 8515402600 4496696391 53% 53340 6805 CGPLBR72 Breast CancerPreoperative, Treatment naïve Y Y 100 80930 8556946900 4389761697 51%52081 5632 CGPLBR73 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 7959392300 4006933338 50% 47555 8791 CGPLBR74 Breast CancerPreoperative, Treatment naïve Y N 100 80930 8524536400 4063900599 48%48252 7013 CGPLBR75 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 8260379100 3960599885 48% 46955 6319 CGPLBR76 Breast CancerPreoperative, Treatment naïve Y Y 100 80930 7774235200 3893622420 50%46192 9628 CGPLBR77 Breast Cancer Preoperative, Treatment naïve Y N 10080930 7572797600 3255963429 43% 38568 8263 CGPLBR80 Breast CancerPreoperative, Treatment naïve Y N 100 80930 6845325800 3147476693 46%37201 5595 CGPLBR82 Breast Cancer Preoperative, Treatment naïve N Y 10080930 8236705200 4170465005 51% 49361 12319 CGPLBR83 Breast CancerPreoperative, Treatment naïve Y Y 100 80930 7434568100 3676855019 49%43628 5458 CGPLBR86 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 7616282500 3644791327 48% 43490 7048 CGPLBR87 Breast CancerPreoperative, Treatment naïve Y Y 100 80930 6194021300 3004882010 49%35765 5306 CGPLBR88 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 6071567200 2847926237 47% 33945 10319 CGPLBR91 Breast CancerPreoperative, Treatment naïve N Y 100 80930 7192457700 3480203404 48%41570 9912 CGPLBR92 Breast Cancer Preoperative, Treatment naïve Y Y 10080930 7678981800 3600279233 47% 42975 13580 CGPLBR93 Breast CancerPreoperative, Treatment naïve N Y 100 80930 7605717800 3998713397 53%47866 10329 CGPLBR96 Breast Cancer Preoperative, Treatment naïve Y N 10080930 6297446700 2463064737 39% 29341 7937 CGPLBR97 Breast CancerPreoperative, Treatment naïve Y N 100 80930 7114921600 3557069027 50%42488 10712 CGPLH35 Healthy Preoperative, Treatment naïve N Y 100 809306919126300 2312758764 33% 25570 1989 CGPLH36 Healthy Preoperative,Treatment naïve N Y 100 80930 6089923400 2038548115 33% 22719 1478CGPLH37 Healthy Preoperative, Treatment naïve N Y 100 80930 55572702001935301929 35% 21673 2312 CGPLH42 Healthy Preoperative, Treatment naïveN Y 100 80930 5792045400 2388036949 41% 27197 2523 CGPLH43 HealthyPreoperative, Treatment naïve N Y 100 80930 5568321700 2017813329 36%23228 1650 CGPLH45 Healthy Preoperative, Treatment naïve N Y 100 809308485593200 2770176078 33% 32829 3114 CGPLH46 Healthy Preoperative,Treatment naïve N Y 100 80930 5083171100 1899395790 37% 21821 1678CGPLH47 Healthy Preoperative, Treatment naïve N Y 100 80930 60163885002062392156 34% 23459 1431 CGPLH48 Healthy Preoperative, Treatment naïveN Y 100 80930 4958945900 1809825992 36% 20702 1698 CGPLH49 HealthyPreoperative, Treatment naïve N Y 100 80930 7953812200 2511365904 32%27006 1440 CGPLH50 Healthy Preoperative, Treatment naïve N Y 100 809306989407600 2561288100 37% 29177 2591 CGPLH51 Healthy Preoperative,Treatment naïve N Y 100 80930 7862073200 2525091396 32% 29999 1293CGPLH52 Healthy Preoperative, Treatment naïve N Y 100 80930 69396368002397922699 35% 27029 2501 CGPLH54 Healthy Preoperative, Treatment naïveN Y 100 80930 10611934700 2290823134 22% 27175 3306 CGPLH55 HealthyPreoperative, Treatment naïve N Y 100 80930 9912569200 2521962244 25%27082 3161 CGRLH56 Healthy Preoperative, Treatment naïve N Y 100 809305777591900 2023874863 35% 22916 1301 CGPLH57 Healthy Preoperative,Treatment naïve N Y 100 80930 9234904800 1493926244 16% 15843 1655CGPLH59 Healthy Preoperative, Treatment naïve N Y 100 80930 97260521002987875484 31% 35427 2143 CGPLH63 Healthy Preoperative, Treatment naïveN Y 100 80930 8696405000 2521574759 29% 26689 1851 CGPLH64 HealthyPreoperative, Treatment naïve N Y 100 80930 5438852600 996198502 18%11477 1443 CGPLH75 Healthy Preoperative, Treatment naïve Y N 100 809303446444000 1505718480 44% 17805 3016 CGPLH76 Healthy Preoperative,Treatment naïve N Y 100 80930 7499116400 3685762725 49% 43682 4643CGPLH77 Healthy Preoperative, Treatment naïve Y N 100 80930 65124084002537359345 39% 30280 3131 CGPLH78 Healthy Preoperative, Treatment naïveN Y 100 80930 7642949300 3946069680 52% 46316 5358 CGPLH79 HealthyPreoperative, Treatment naïve N Y 100 80930 7785475700 3910639227 50%45280 6714 CGPLH80 Healthy Preoperative, Treatment naïve N Y 100 809307918361500 3558236955 45% 42171 5062 CGPLH81 Healthy Preoperative,Treatment naïve Y N 100 80930 6646268900 3112369850 47% 37119 3678CGPLH82 Healthy Preoperative, Treatment naïve N Y 100 80930 77440650003941700596 51% 46820 5723 CGPLH83 Healthy Preoperative, Treatment naïveY N 100 80930 6957686000 1447603106 21% 17280 2875 CGPLH84 HealthyPreoperative, Treatment naïve Y N 100 80930 8326493200 3969908122 48%47464 3647 CGPLH86 Healthy Preoperative, Treatment naïve N Y 100 809308664194700 4470145091 52% 53398 5094 CGPLH90 Healthy Preoperative,Treatment naïve N Y 100 80930 7516078800 3841504088 51% 45907 4414CGPLLU13 Lung Cancer Pre-treatment, Day −2 Y N 100 80930 56595461001721618955 30% 20587 6025 CGPLLU13 Lung Cancer Pre-treatment, Day −2 Y N100 80930 6199049700 2563659840 41% 30728 6514 CGPLLU13 Lung CancerPre-treatment, Day −2 Y N 100 80930 5864396500 1194237002 20% 14331 3952CGPLLU13 Lung Cancer Pre-treatment, Day −2 Y N 100 80930 50801977001373550586 27% 16480 5389 CGPLLU14 Lung Cancer Pre-treatment, Day −38 NY 100 80930 8668655700 398731089 46% 48628 3148 CGPLLU14 Lung CancerPre-treatment, Day −16 N Y 100 80930 8271043600 4105092738 50% 501524497 CGPLLU14 Lung Cancer Pre-treatment, Day −3 N Y 100 80930 71498092003405754720 48% 40382 6170 CGPLLU14 Lung Cancer Pre-treatment, Day 0 N Y100 80930 6556332200 3289504484 50% 39004 4081 CGPLLU14 Lung CancerPost-treatment, Day 0.33 N Y 100 80930 7410378300 3464236558 47% 411084259 CGPLLU14 Lung Cancer Post-treatment, Day 7 N Y 100 80930 75301907003752054349 50% 45839 2469 CGPLLU144 Lung Cancer Preoperative, Treatmentnaïve Y Y 100 80930 8716827400 4216576624 48% 49370 10771 CGPLLU146 LungCancer Preoperative, Treatment naïve Y N 100 80930 8506844200 419503304949% 49084 6968 CGPLLU147 Lung Cancer Preoperative, Treatment naïve Y N100 80930 7416300600 3530746046 48% 41302 4691 CGPLLU161 Lung CancerPreoperative, Treatment naïve N Y 100 80930 7789148700 3280139772 42%38568 12229 CGPLLU162 Lung Cancer Preoperative, Treatment naïve Y Y 10080930 7625462000 3470147667 46% 40918 10099 CGPLLU163 Lung CancerPreoperative, Treatment naïve Y Y 100 80930 8019293200 3946533983 49%46471 12108 CGPLLU164 Lung Cancer Preoperative, Treatment naïve Y N 10080930 8110030900 3592748235 44% 42161 6947 CGPLLU165 Lung CancerPreoperative, Treatment naïve Y N 100 80930 8389514600 4147501817 49%48770 8996 CGPLLU168 Lung Cancer Preoperative, Treatment naïve Y Y 10080930 7600630000 3868237773 50% 45625 9711 CGPLLU169 Lung CancerPreoperative, Treatment naïve N Y 100 80930 9378353000 4800407624 51%56547 10261 CGPLLU174 Lung Cancer Preoperative, Treatment naïve Y N 10080930 7481844600 3067532518 41% 36321 6137 CGPLLU175 Lung CancerPreoperative, Treatment naïve Y N 100 80930 8532324200 4002541569 47%47084 7862 CGPLLU176 Lung Cancer Preoperative, Treatment naïve Y Y 10080930 8143905000 4054098929 50% 47708 5588 CGPLLU177 Lung CancerPreoperative, Treatment naïve Y Y 100 80930 8421611300 4197108809 50%49476 8780 CGPLLU178 Lung Cancer Preoperative, Treatment naïve Y N 10080930 8483124700 4169577489 49% 48580 6445 CGPLLU179 Lung CancerPreoperative, Treatment naïve Y N 100 80930 7774358700 3304915738 43%38768 6862 CGPLLU180 Lung Cancer Preoperative, Treatment naïve Y N 10080930 8192813800 3937552475 48% 46498 6568 CGPLLU197 Lung CancerPreoperative, Treatment naïve Y N 100 80930 7906779200 3082397881 39%36381 5388 CGPLLU198 Lung Cancer Preoperative, Treatment naïve Y N 10080930 7175247200 3545719100 49% 42008 6817 CGPLLU202 Lung CancerPreoperative, Treatment naïve Y N 100 80930 6840112800 3427820669 50%40670 7951 CGPLLU203 Lung Cancer Preoperative, Treatment naïve N Y 10080930 7458749900 3762726574 50% 44500 9917 CGPLLU204 Lung CancerPreoperative, Treatment naïve Y N 100 80930 7445026400 3703545153 50%44317 6856 CGPLLU205 Lung Cancer Preoperative, Treatment naïve Y Y 10080930 9205429100 4350573991 47% 51627 9810 CGPLLU206 Lung CancerPreoperative, Treatment naïve Y N 100 80930 7397914600 3635210205 49%43016 7124 CGPLLU207 Lung Cancer Preoperative, Treatment naïve Y Y 10080930 7133043900 3736258011 52% 44291 8499 CGPLLU208 Lung CancerPreoperative, Treatment naïve Y Y 100 80930 7346976400 3855814032 52%45782 8940 CGPLLU209 Lung Cancer Preoperative, Treatment naïve Y N 10080930 6723337800 3362944595 50% 39531 11946 CGPLLU244 Lung CancerPre-treatment Day −7 N Y 100 80930 8305560600 4182616104 50% 50851 7569CGPLLU244 Lung Cancer Pre-treatment, Day −1 N Y 100 80930 77399511003788487116 49% 45925 8552 CGPLLU244 Lung Cancer Post-treatment, Day 6 NY 100 80930 8061928000 4225322272 52% 51279 8646 CGPLLU244 Lung CancerPost-treatment, Day 62 N Y 100 80930 8894936700 4437962639 50% 538627361 CGPLLU245 Lung Cancer Pre-treatment, Day −32 N Y 100 809307679235200 3935822054 51% 47768 7266 CGPLLU245 Lung Cancer Pre-treatmentDay 0 N Y 100 80930 8985252500 4824268339 54% 58338 10394 CGPLLU245 LungCancer Post-treatment, Day 7 N Y 100 80930 8518229300 4480236927 53%54083 10125 CGPLLU245 Lung Cancer Post-treatment, Day 21 N Y 100 809309031131000 4824738475 53% 58313 10598 CGPLLU246 Lung CancerPre-treatment. Day −21 N Y 100 80930 8520360800 3509660305 41% 423498086 CGPLLU246 Lung Cancer Pre-treatment, Day 0 N Y 100 80930 54514678002828351657 52% 34243 8256 CGPLLU246 Lung Cancer Post-treatment, Day 9 NY 100 80930 8137616600 4135036174 51% 50121 6466 CGPLLU246 Lung CancerPost-treatment, Day 42 N Y 100 80930 8385724600 4413323333 53% 534957303 CGPLLU264 Lung Cancer Pre-treatment, Day −1 Y N 100 809306254777700 3016326208 48% 36164 12138 CGPLLU264 Lung CancerPre-treatment, Day −1 Y N 100 80930 6185331000 3087883231 50% 37003 8388CGPLLU264 Lung Cancer Pre-treatment, Day −1 Y N 100 80930 62745403002861143666 46% 34308 6817 CGPLLU264 Lung Cancer Pre-treatment, Day −1 YN 100 80930 5701274000 1241270938 22% 14886 4273 CGPLLU265 Lung CancerPre-treatment, Day 0 Y N 100 80930 6091276800 2922585558 48% 35004 7742CGPLLU265 Lung Cancer Pre-treatment, Day 0 Y N 100 80930 64301079002945953499 46% 35219 8574 CGPLLU265 Lung Cancer Pre-treatment, Day 0 Y N100 80930 5869510300 2792208995 48% 33423 8423 CGPLLU265 Lung CancerPre-treatment, Day 0 Y N 100 80930 5884330900 2588386038 44% 30977 9803CGPLLU266 Lung Cancer Pre-treatment, Day 0 Y N 100 80930 58075249002347651479 40% 28146 5793 CGPLLU266 Lung Cancer Pre-treatment, Day 0 Y N100 80930 6064269800 2086938782 34% 24994 6221 CGPLLU266 Lung CancerPre-treatment, Day 0 Y N 100 80930 6785913900 3458588505 51% 41432 7785CGPLLU266 Lung Cancer Pre-treatment, Day 0 Y N 100 80930 65137020002096370387 32% 25142 6598 CGPLLU267 Lung Cancer Pre-treatment, Day −1 YN 100 80930 6610761200 2576886619 39% 31095 4485 CGPLLU267 Lung CancerPre-treatment, Day −1 Y N 100 80930 6156402000 2586081726 42% 30714 5309CGPLLU267 Lung Cancer Pre-treatment, Day −1 Y N 100 80930 61807997002013434756 33% 23902 3885 CGPLLU269 Lung Cancer Pre-treatment, Day 0 Y N100 80930 6221168600 1499602843 24% 17799 6098 CGPLLU269 Lung CancerPre-treatment, Day 0 Y N 100 80930 5353961600 1698331125 32% 20094 5252CGPLLU269 Lung Cancer Pre-treatment, Day 0 Y N 100 80930 58316128001521114956 26% 18067 6210 CGPLLU271 Lung Cancer Post-treatment, Day 259Y N 100 80930 6229704000 1481468974 24% 17608 4633 CGPLLU271 Lung CancerPost-treatment, Day 259 Y N 100 80930 6134366400 1351029627 22% 161707024 CGPLLU271 Lung Cancer Post-treatment, Day 259 Y N 100 809306491884900 1622578435 25% 19433 5792 CGPLLU271 Lung CancerPost-treatment, Day 259 Y N 100 80930 5742881200 2349421128 41% 281715723 CGPLLU271 Lung Cancer Post-treatment, Day 259 Y N 100 809305503999300 1695782705 31% 20320 5907 CGPLLU43 Lung Cancer Pre-treatment,Day −1 Y N 100 80930 6575907000 3002048491 46% 35997 5445 CGPLLU43 LungCancer Pre-treatment, Day −1 Y N 100 80930 6204350900 3016077187 49%36162 5704 CGPLLU43 Lung Cancer Pre-treatment, Day −1 Y N 100 809305997724300 2989608757 50% 35873 6228 CGPLLU43 Lung Cancer Pre-treatment,Day −1 Y N 100 80930 6026261500 2881177658 48% 34568 7221 CGPLLU86 LungCancer Pre-treatment, Day 0 N Y 100 80930 8222093400 3523035056 43%41165 3614 CGPLLU86 Lung Cancer Post-treatment, Day 0.5 N Y 100 809308305719500 4271264008 51% 49508 6681 CGPLLU86 Lung CancerPost-treatment, Day 7 N Y 100 80930 6787785300 3443658418 51% 40192 3643CGPLLU86 Lung Cancer Post-treatment, Day 17 N Y 100 80930 62132294003120325926 50% 36413 3560 CGPLLU88 Lung Cancer Pre-treatment, Day 0 Y N100 80930 7252433900 3621678746 50% 42719 8599 CGPLLU88 Lung CancerPre-treatment, Day 0 Y N 100 80930 7679995800 4004738253 52% 46951 6387CGPLLU88 Lung Cancer Pre-treatment, Day 0 Y N 100 80930 65091780003316053733 51% 39274 2651 CGPLLU89 Lung Cancer Pre-treatment, Day 0 N Y100 80930 7662496600 3781536306 49% 44097 7909 CGPLLU89 Lung CancerPost-treatment, Day 7 N Y 100 80930 7005599600 3339612564 48% 38977 5034CGPLLU89 Lung Cancer Post-treatment, Day 22 N Y 100 80930 83259986003094796789 37% 36061 2822 CGPLOV10 Ovarian Cancer Preoperative,Treatment naïve Y Y 100 80930 7073534200 3402306123 48% 39820 4059CGPLOV11 Ovarian Cancer Preoperative, Treatment naïve Y Y 100 809306924062200 3324593050 48% 38796 7185 CGPLOV12 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 6552080100 3181854993 49%37340 6114 CGPLOV13 Ovarian Cancer Preoperative, Treatment naïve Y Y 10080930 6796755500 3264897084 48% 38340 7931 CGPLOV14 Ovarian CancerPreoperative, Treatment naïve Y Y 100 80930 7856573900 3408425065 43%39997 7712 CGPLOV15 Ovarian Cancer Preoperative, Treatment naïve Y Y 10080930 7239201500 3322285607 46% 38953 6644 CGPLOV16 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 8570755900 4344288233 51%51009 11947 CGPLOV17 Ovarian Cancer Preoperative, Treatment naïve Y N100 80930 6910310400 2805243492 41% 32828 4307 CGPLOV18 Ovarian CancerPreoperative, Treatment naïve N N 100 80930 8173037600 4064432407 50%47714 5182 CGPLOV19 Ovarian Cancer Preoperative, Treatment naïve Y Y 10080930 7732198900 3672564399 47% 43020 11127 CGPLOV20 Ovarian CancerPreoperative, Treatment naïve Y Y 100 80930 7559602000 3678700179 49%43230 4872 CGPLOV21 Ovarian Cancer Preoperative, Treatment naïve Y Y 10080930 8949032900 4616255499 52% 54012 12777 CGPLOV22 Ovarian CancerPreoperative, Treatment naïve Y Y 100 80930 8680136500 4049934586 47%46912 9715 CGPLOV23 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 6660696600 3422631774 51% 40810 9460 CGPLOV24 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 8634287200 4272258165 49%50736 8689 CGPLOV25 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 6978295000 3390206388 49% 40188 5856 CGPLOV26 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 7041038300 3728879661 53%44341 8950 CGPLOV28 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 7429236900 3753051715 51% 45430 4155 CGPLOV31 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 8961384000 4621838729 51%55429 5458 CGPLOV32 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 9344536800 4737698323 51% 57234 6165 CGPLOV37 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 8158083200 4184432898 51%50648 6934 CGPLOV38 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 8654435400 4492987085 52% 53789 6124 CGPLOV40 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 9868640700 4934400809 50%59049 7721 CGPLOV41 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 7689013600 3861448829 50% 46292 4469 CGPLOV42 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 9836516300 4864154366 49%58302 7632 CGPLOV43 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 8756507100 4515479918 52% 54661 4310 CGPLOV44 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 7576310800 4120933922 54%49903 4969 CGPLOV46 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 9346036300 5037820346 54% 61204 3927 CGPLOV47 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 10880620200 5491357828 50%66363 6895 CGPLOV48 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 7658787800 3335991337 44% 40332 4066 CGPLOV49 Ovarian CancerPreoperative, Treatment naïve N Y 100 80930 10076208000 5519656698 55%67117 5097 CGPLOV50 Ovarian Cancer Preoperative, Treatment naïve N Y 10080930 8239290400 4472380276 54% 54150 3836 CGPLPA118 Bile Duct CancerPreoperative, Treatment naïve N Y 100 80930 9094827600 4828332902 53%57021 4002 CGPLPA122 Bile Duct Cancer Preoperative, Treatment naïve N Y100 80930 7303323100 3990160379 55% 47240 7875 CGPLPA124 Bile DuctCancer Preoperative, Treatment naïve N Y 100 80930 7573482800 396580744252% 46388 8658 CGPLPA126 Bile Duct Cancer Preoperative, Treatment naïveN Y 100 80930 7904953600 4061463168 51% 47812 10498 CGPLPA128 Bile DuctCancer Preoperative, Treatment naïve N Y 100 80930 7249238300 224418873531% 26436 3413 CGPLPA129 Bile Duct Cancer Preoperative, Treatment naïveN Y 100 80930 7559858900 4003725804 53% 47182 5733 CGPLPA130 Bile DuctCancer Preoperative, Treatment naïve N Y 100 80930 6973946500 124714490518% 14691 1723 CGPLPA131 Bile Duct Cancer Preoperative, Treatment naïveN Y 100 80930 7226237900 3370664342 47% 39661 5054 CGPLPA134 Bile DuctCancer Preoperative, Treatment naïve N Y 100 80930 7268866100 375494584452% 44306 7023 CGPLPA136 Bile Duct Cancer Preoperative, Treatment naïveN Y 100 80930 7476690700 4073978408 54% 48134 5244 CGPLPA140 Bile DuctCancer Preoperative, Treatment naïve N Y 100 80930 7364654600 377176534251% 44479 7080 CGST102 Gastric Cancer Preoperative, Treatment naïve N Y100 80930 5715504500 2644902854 46% 31309 4503 CGST110 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 9179291500 4298269268 47%51666 3873 CGST114 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 7151572200 3254967293 46% 38496 4839 CGST13 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 6449701500 3198545984 50%38515 6731 CGST141 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 6781001300 3440927391 51% 40762 5404 CGST16 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 6396470600 2931380289 46%35354 8148 CGST18 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 6647324000 3138967777 47% 37401 4992 CGST28 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 6288486100 2884997993 46%34538 2586 CGST30 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 6141213100 3109994564 51% 37194 2555 CGST32 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 6969139300 3099120469 44%36726 3935 CGST33 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 6560309400 3168371917 48% 37916 4597 CGST39 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 7043791400 2992501875 42%35620 6737 CGST41 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 6975053100 3224065662 46% 38300 4016 CGST45 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 6130812200 2944524278 48%35264 4745 CGST47 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 5961400000 3083523351 52% 37008 3112 CGST48 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 6418652700 1497230327 23%17782 2410 CGST58 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 5818344500 1274708429 22% 15281 2924 CGST80 Gastric CancerPreoperative, Treatment naïve N Y 100 80930 6388064600 3298497188 52%39692 5280 CGST81 Gastric Cancer Preoperative, Treatment naïve N Y 10080930 8655691400 1519121452 18% 17988 6419

APPENDIX C Table 3. Targeted cfDNA fragment analyses in cancer patientsStage at Amino Acid Patient Patient Type Diagnosis Alteration Type Gene(Protein) CGCRC291 Colorectal Cancer IV Tumor-derived STK11 39R > CCGCRC291 Colorectal Cancer IV Tumor-derived TP53 272V > M CGCRC291Colorectal Cancer IV Tumor-derived TP53 167Q > X CGCRC291 ColorectalCancer IV Tumor-derived KRAS 12G > A CGCRC291 Colorectal Cancer IVTumor-derived APC 1260Q > X CGCRC291 Colorectal Cancer IV Tumor-derivedAPC 1450R > X CGCRC291 Colorectal Cancer IV Tumor-derived PIK3CA 542E >K CGCRC292 Colorectal Cancer IV Tumor-derived KRAS 146A > V CGCRC292Colorectal Cancer IV Tumor-derived CTNNB1 41T > A CGCRC292 ColorectalCancer IV Germline EGFR 2284 − 4C > 3 CGCRC293 Colorectal Cancer IVTumor-derived TP53 176C > S CGCRC294 Colorectal Cancer II Tumor-derivedAPC 213R > X CGCRC294 Colorectal Cancer II Tumor-derived APC 1367Q > XCGCRC295 Colorectal Cancer IV Tumor-derived PDBFRA 49 + 4C > T CGCRC295Colorectal Cancer IV Hematopoietic IDH1 104G > V CGCRC296 ColorectalCancer II Germline EGFR 922E > K CGCRC297 Colorectal Cancer III GermlineKIT 18L > F CGCRC298 Colorectal Cancer II Hematopoietic DNMT3A 882R > HCGCRC298 Colorectal Cancer II Hematopoietic DNMT3A 714S > C CGCRC298Colorectal Cancer II Tumor-derived PIK3CA 414G > V CGCRC299 ColorectalCancer I Hematopoietic DNMT3A 735Y > C CGCRC299 Colorectal Cancer IHematopoietic DNMT3A 710C > S CGCRC300 Colorectal Cancer I HematopoieticDNMT3A 720R > G CGCRC301 Colorectal Cancer I Tumor-derived ATM 2397Q > XCGCRC302 Colorectal Cancer II Tumor-derived TP53 141C > Y CGCRC302Colorectal Cancer II Tumor-derived BRAF 600V > E CGCRC303 ColorectalCancer III Tumor-derived TP53 173V > L CGCRC303 Colorectal Cancer IIIHematopoietic DNMT3A 755F > S CGCRC303 Colorectal Cancer IIIHematopoietic DNMT3A 2173 + 1G > A CGCRC304 Colorectal Cancer IITumor-derived EGFR 1131T > S CGCRC304 Colorectal Cancer II Tumor-derivedATM 3077 + 1G > A CGCRC304 Colorectal Cancer II Hematopoietic ATM3008R > C CGCRC305 Colorectal Cancer II Tumor-derived GNA11 213R > QCGCRC305 Colorectal Cancer II Tumor-derived TP53 273R > H CGCRC306Colorectal Cancer II Tumor-derived TP53 196R > X CGCRC306 ColorectalCancer II Tumor-derived CDKN2A 107R > C CGCRC306 Colorectal Cancer IITumor-derived KRAS 61Q > K CGCRC306 Colorectal Cancer II Germline PDGFRA200T > S CGCRC306 Colorectal Cancer II Tumor-derived EGFR 618H > RCGCRC306 Colorectal Cancer II Tumor-derived PIK3CA 545E > A CGCRC306Colorectal Cancer II Germline ERBB4 1155R > X CGCRC307 Colorectal CancerII Tumor-derived JAK2 805L > V CGCRC307 Colorectal Cancer IITumor-derived SMARCB1 501 − 2A > G CGCRC307 Colorectal Cancer IITumor-derived GNAS 201R > C CGCRC307 Colorectal Cancer II Tumor-derivedBRAF 600V > E CGCRC307 Colorectal Cancer II Tumor-derived FBXW7 465R > CCGCRC307 Colorectal Cancer II Tumor-derived ERBB4 17A > V CGCRC308Colorectal Cancer III Hematopoietic DNMT3A 882R > H CGCRC308 ColorectalCancer III Germline EGFR 848P > L CGCRC308 Colorectal Cancer IIITumor-derived APC 1480Q > X CGCRC309 Colorectal Cancer III Tumor-derivedAKT1 17E > K CGCRC309 Colorectal Cancer III Tumor-derived BRAF 600V > ECGCRC310 Colorectal Cancer II Tumor-derived KRAS 12G > V CGCRC310Colorectal Cancer II Tumor-derived APC 1513E > X CGCRC310 ColorectalCancer II Tumor-derived APC 1521E > X CGCRC311 Colorectal Cancer IHematopoietic DNMT3A 882R > H CGCRC312 Colorectal Cancer IIITumor-derived APC 960S > X CGCRC312 Colorectal Cancer III Tumor-derivedNRAS 61Q > K CGCRC313 Colorectal Cancer III Tumor-derived KRAS 12G > SCGCRC313 Colorectal Cancer III Tumor-derived APC 876R > X CGCRC314Colorectal Cancer I Tumor-derived KRAS 12G > D CGCRC314 ColorectalCancer I Hematopoietic DNMT3A 738L > Q CGCRC314 Colorectal Cancer ITumor-derived APC 1379E > X CGCRC315 Colorectal Cancer III Tumor-derivedNRAS 12G > D CGCRC315 Colorectal Cancer III Tumor-derived FBXW7 505R > CAlteration Mutant Mutation Hotspot Detected Allele Patient NucleotideType Alteration in Tissue Fraction CGCRC291 chr19_1207027-127027_C_TSubstitution No No 0.14% CGCRC291 chr17_7577124-7577124_C_T SubstitutionYes No 0.10% CGCRC291 chr17_7578431-7578431_G_A Substitution Yes Yes22.85% CGCRC291 chr12_25398284-25398284_C_G Substitution Yes Yes 14.65%CGCRC291 chr5_112175069-112175069_C_T Substitution No Yes 11.23%CGCRC291 chr5_11215639-11215639_C_T Substitution Yes Yes 11.05% CGCRC291chr3_178936082-178936082_G_A Substitution Yes Yes 18.11% CGCRC292chr12_25378561-25378561_G_A Substitution Yes No 1.41% CGCRC292chr3_41266124-41266124_A_G Substitution Yes Yes 0.13% CGCRC292chr7_55248982-55248982_C_G Substitution NA Yes 31.99% CGCRC293chr17_7578404-7578404_A_T Substitution No No 0.35% CGCRC294chr5_12116592-12116592_C_T Substitution Yes Yes 0.14% CGCRC294chr5_12175390-12175390_C_T Substitution Yes Yes 0.13% CGCRC295chr4_55124988-55124988_C_T Substitution No No 0.45% CGCRC295chr2_209113196-209113196_C_A Substitution No Yes 0.34% CGCRC296chr7_55266472-55266472_G_A Substitution NA Yes 30.48% CGCRC297chr4_55524233-55524233_C_T Substitution NA Yes 41.39% CGCRC298chr2_25457242-25457242_C_T Substitution Yes Yes 0.08% CGCRC298chr2_25463541-25463541_G_C Substitution No No 0.11% CGCRC298chr3_178927478-178927478_G_T Substitution No No 0.55% CGCRC299chr2_25463289-25463289_T_C Substitution No Yes 0.30% CGCRC299chr2_25463553-2546355_C_G Substitution No Yes 0.12% CGCRC300chr2_25463524-25463524_G_C Substitution No No 0.15% CGCRC301chr11_108199847-108199847_C_T Substitution No No 0.21% CGCRC302chr17_7578508-7578508_C_T Substitution Yes Yes 0.05% CGCRC302chr7_140453136-140453136_A_T Substitution Yes Yes 0.12% CGCRC303chr17_7578413-7578413_C_A Substitution Yes Yes 0.08% CGCRC303chr2_25463229-25463229_A_G Substitution No No 0.21% CGCRC303chr2_25463508-25463508_C_T Substitution No No 0.17% CGCRC304chr7_55273068-55273068_A_T Substitution No No 0.22% CGCRC304chr11_108142134-108142134_G_A Substitution No No 0.27% CGCRC304chr11_108236086-108236086_C_T Substitution No Yes 0.43% CGCRC305chr19_3118954-3118954_G_A Substitution No Yes 0.11% CGCRC305chr17_7577120-7577120_C_T Substitution Yes No 0.19% CGCRC306chr17_7578263-7578263_G_A Substitution Yes No 0.12% CGCRC306chr9_21971039-21971039_G_A Substitution No Yes 8.02% CGCRC306chr12_25380277-25380277_G_T Substitution Yes Yes 7.30% CGCRC306chr4_55130065-55130065_C_G Substitution NA Yes 34.78% CGCRC306chr7_55233103-55233103_A_G Substitution No Yes 8.32% CGCRC306chr3_178936092-178936092_A_C Substitution Yes No 0.96% CGCRC306chr2_2122596-2122596_G_A Substitution NA Yes 38.70% CGCRC307chr9_5080662-5080662_C_G Substitution No No 0.56% CGCRC307chr22_24145480-24145480_A_G Substitution No Yes 0.34% CGCRC307chr20_57484420-57484420_C_T Substitution Yes  Yes# 0.24% CGCRC307chr7_140453136-140453136_A_T Substitution Yes Yes 0.38% CGCRC307chr4_153249385-153249385_G_A Substitution Yes Yes 0.31% CGCRC307chr2_213403205-213403205_G_A Substitution No No 0.15% CGCRC308chr2_25457242-25457242_C_T Substitution Yes No 0.06% CGCRC308chr7_55259485-55259485_C_T Substitution NA Yes 27.69% CGCRC308chr5_112175242-112175242_C_T Substitution No Yes 0.11% CGCRC309chr14_105246551-105246551_C_T Substitution Yes Yes 2.70% CGCRC309chr7_140453136-140453136_A_T Substitution Yes Yes 3.00% CGCRC310chr12_25398284-25398284_C_A Substitution Yes Yes 0.13% CGCRC310chr5_11215828-11215828_G_T Substitution No Yes 0.11% CGCRC310chr5_11215852-11215852_G_T Substitution No Yes 0.15% CGCRC311chr2_25457242-25457242_C_T Substitution Yes No 0.86% CGCRC312chr5_112174170-112174170_C_G Substitution No Yes 0.59% CGCRC312chr1_115256530-115256530_G_T Substitution Yes Yes 0.47% CGCRC313chr12_25398285-25398285_C_T Substitution Yes Yes 0.17% CGCRC313chr5_112173917-112173917_C_T Substitution Yes Yes 0.07% CGCRC314chr12_25398284-25398284_C_T Substitution Yes Yes 0.30% CGCRC314chr2_25463280-25463280_A_T Substitution No Yes 2.50% CGCRC314chr5_112175426-112175426_G_T Substitution Yes Yes 0.38% CGCRC315chr1_115258747-115258747_C_T Substitution Yes Yes 0.27% CGCRC315chr4_153247289-53247289_G_A Substitution Yes Yes 0.25% Wild-typeFragments 25th Minimum Percentile Mode Median cfDNA cfDNA cfDNA cfDNAFragment Fragment Fragment Fragment Distinct Size Size Size Size PatientCoverage (bp) (bp) (bp) (bp) CGCRC291 11688 100 151 167 159 CGCRC29111779 100 155 171 159 CGCRC291 11026 100 156 166 159 CGCRC291 7632 97152 169 157 CGCRC291 7218 101 155 167 159 CGCRC291 10757 86 154 166 167CGCRC291 5429 100 151 171 167 CGCRC292 8120 101 157 167 169 CGCRC29210693 100 155 169 168 CGCRC292 7587 97 158 166 171 CGCRC293 7672 95 159168 170 CGCRC294 7339 84 155 166 167 CGCRC294 12054 89 159 167 170CGCRC295 5602 101 157 164 170 CGCRC295 8330 100 157 166 169 CGCRC2968375 89 161 166 172 CGCRC297 3580 102 159 164 170 CGCRC298 13032 100 159168 171 CGCRC298 13475 93 158 169 170 CGCRC298 5815 100 156 168 169CGCRC299 11995 100 154 164 165 CGCRC299 15363 96 151 166 164 CGCRC3007487 100 162 170 173 CGCRC301 5881 100 156 169 169 CGCRC302 24784 84 154165 164 CGCRC302 11763 95 159 165 165 CGCRC303 13967 95 160 169 171CGCRC303 10161 81 160 169 172 CGCRC303 10845 100 160 169 172 CGCRC30416168 90 153 167 164 CGCRC304 10502 100 152 165 163 CGCRC304 12987 101154 165 165 CGCRC305 12507 100 159 169 171 CGCRC305 10301 100 156 168168 CGCRC306 8594 101 157 165 169 CGCRC306 9437 90 159 167 171 CGCRC3068090 100 152 163 168 CGCRC306 4585 103 158 167 170 CGCRC306 7395 81 160166 171 CGCRC306 4885 100 152 167 167 CGCRC306 3700 100 159 166 171CGCRC307 6860 100 158 170 170 CGCRC307 10065 95 157 168 169 CGCRC3077520 102 156 167 168 CGCRC307 6623 76 157 169 168 CGCRC307 10606 100 155167 168 CGCRC307 13189 90 158 168 171 CGCRC308 16287 90 159 168 169CGCRC308 7729 100 160 164 170 CGCRC308 14067 92 157 170 169 CGCRC30913036 85 157 170 169 CGCRC309 9084 101 157 166 168 CGCRC310 7393 100 153165 164 CGCRC310 11689 100 152 166 164 CGCRC310 10273 100 153 166 164CGCRC311 8456 94 160 171 172 CGCRC312 4719 100 160 165 173 CGCRC312 3391101 157 172 170 CGCRC313 5013 100 163 166 174 CGCRC313 8150 72 161 171174 CGCRC314 4684 100 158 165 169 CGCRC314 6902 85 159 165 170 CGCRC3147229 102 158 167 170 CGCRC315 8739 94 155 167 169 CGCRC315 9623 101 158166 170 Stage at Amino Acid Patient Patient Type Diagnosis AlterationType Gene (Protein) CGCRC316 Colorectal Cancer III Tumor-derived TP53245G > S CGCRC316 Colorectal Cancer III Tumor-derived CDKN2A 1M > RCGCRC316 Colorectal Cancer III Tumor-derived CTNNB1 37S > C CGCRC316Colorectal Cancer III Tumor-derived EGFR 2732 − 3C > T CGCRC316Colorectal Cancer III Hematopoietic ATM 3008R > P CGCRC317 ColorectalCancer III Tumor-derived TP53 220Y > C CGCRC317 Colorectal Cancer IIITumor-derived ATM 1026W > R CGCRC317 Colorectal Cancer III Tumor-derivedAPC 216R > X CGCRC318 Colorectal Cancer I Hematopoietic DNMT3A 698W > XCGCRC320 Colorectal Cancer I Germline KIT 18L > F CGCRC320 ColorectalCancer I Tumor-derived ERBB4 78R > W CGCRC321 Colorectal Cancer ITumor-derived CDKN2A 12S > L CGCRC321 Colorectal Cancer I HernatopcieticDNMT3A 882R > H CGCRC321 Colorectal Cancer I Germline EGFR 511S > YCGCRC332 Colorectal Cancer IV Tumor-derived TP53 125T > R CGCRC333Colorectal Cancer IV Tumor-derived TP53 673 − 2A > G CGCRC333 ColorectalCancer IV Tumor-derived BRAF 600V > E CGCRC333 Colorectal Cancer IVTumor-derived ERBB4 891E > A CGCRC334 Colorectal Cancer IV Tumor-derivedTP53 245G > S CGCRC334 Colorectal Cancer IV Germline EGFR 638T > MCGCRC334 Colorectal Cancer IV Tumor-derived PIK3CA 104P > R CGCRC335Colorectal Cancer IV Tumor-derived BRAF 600V > E CGCRC336 ColorectalCancer IV Tumor-derived TP53 175R > H CGCRC336 Colorectal Cancer IVTumor-derived KRAS 12G > V CGCRC336 Colorectal Cancer IV Tumor-derivedAPC 1286E > X CGCRC337 Colorectal Cancer IV Tumor-derived STK11 734 +ST > A CGCRC337 Colorectal Cancer IV Germline APC 485M > I OGORC338Colorectal Cancer IV Tumor-derived KRAS 12G > D CGCRC339 ColorectalCancer IV Tumor-derived KRAS 13G > D CGCRC339 Colorectal Cancer IVTumor-derived APC 876R > X CGCRC339 Colorectal Cancer IV Tumor-derivedPIK3CA 407C > F CGCRC339 Colorectal Cancer IV Tumor-derived PIK3CA1047H > L CGCRC340 Colorectal Cancer IV Tumor-derived TP53 196R > XCGCRC340 Colorectal Cancer IV Tumor-derived APC 1306E > X CGPLBR38Breast Cancer I Tumor-derived TP53 241S > P CGPLBR40 Breast Cancer IIIGermline AR 392P > R CGPLBR44 Breast Cancer III Hematopoietic DNMT3A882R > H CGPLBR44 Breast Cancer III Hematopoietic DNMT3A 705I > TCGPLBR44 Breast Cancer III Tumor-derived PDGFRA 859V > M CGPLBR48 BreastCancer II Germline ALK 1231R > Q CGPLBR48 Breast Cancer II Tumor-derivedEGFR 669R > Q CGPLBR55 Breast Cancer III Hematopoietic DNMT3A 743P > SCGPLBR55 Breast Cancer III Tumor-derived GNAS 201R > H CGPLBR55 BreastCancer III Tumor-derived PIK3CA 345N > K CGPLBR63 Breast Cancer IIGermline FGFR3 403K > E CGPLBR67 Breast Cancer II Hematopoietic DNMT3A882R > H CGPLBR67 Breast Cancer II Tumor-derived PIK3CA 545E > KCGPLBR67 Breast Cancer II Tumor-derived ERBB4 1000D > A CGPLBR69 BreastCancer II Hematopoietic DNMT3A 774E > V CGPLBR69 Breast Cancer IIGermline CTNNB1 30Y > S CGPLBR69 Breast Cancer II Germline IDH1 231Y > NCGPLBR70 Breast Cancer II Tumor-derived ATM 2832R > H CGPLBR70 BreastCancer II Germline APC 1577E > D CGPLBR71 Breast Cancer II Tumor-derivedTP53 273R > H CGPLBR72 Breast Cancer II Germline APC 1532D > G CGPLBR73Breast Cancer II Tumor-derived ALK 708S > P CGPLBR73 Breast Cancer IIGermline ERBB4 158A > E CGPLBR74 Breast Cancer II Germline AR 20 + G1G >T CGPLBR75 Breast Cancer II Tumor-derived PIK3CA 1047H > R CGPLBR76Breast Cancer II Germline KDR 1290S > N CGPLBR76 Breast Cancer IITumor-derived PIK3CA 1047H > R CGPLBR77 Breast Cancer III Tumor-derivedPTEN 170S > I CGPLBR80 Breast Cancer II Tumor-derived CDKN2A 12S > LCGPLBR83 Breast Cancer II Germline AR 728N > D CGPLBR83 Breast Cancer IITumor-derived ATM 322E > K CGPLBR83 Breast Cancer II Germline ERBB4539Y > S CGPLBR86 Breast Cancer II Germline STK11 354F > L AlterationMutant Mutation Hotspot Detected Allele Patient Nucleotide TypeAlteration in Tissue Fraction CGCRC316 chr17_7577548-7577548_C_TSubstitution Yes Yes 6.52% CGCRC316 chr9_21974625-21974825_A_CSubstitution No Yes 5.74% CGCRC316 chr3_41266113-41266113_C_GSubstitution Yes Yes 5.47% CGCRC316 chr7_55266407-55266407_C_TSubstitution No No 0.11% CGCRC316 chr11_108236087-108236087_G_CSubstitution No Yes 0.13% CGCRC317 chr17_7578190-7578190_T_CSubstitution Yes Yes 0.36% CGCRC317 chr11_108142132-108142132_T_CSubstitution No Yes 0.23% CGCRC317 chr5_112128143-112128143_C_TSubstitution Yes No 0.29% CGCRC318 chr2_25463589-25463589_C_TSubstitution No Yes 0.25% CGCRC320 chr4_55524233-55524233_C_TSubstitution NA Yes 34.76% CGCRC320 chr2_212989479-212989479_G_ASubstitution No No 0.12% CGCRC321 chr9_21974792-21974792_C_TSubstitution No No 0.20% CGCRC321 chr2_25457242-25457242_C_ASubstitution You No 0.08% CGCRC321 chr7_55229225-55229225_G_CSubstitution NA Yes 41.86% CGCRC332 chr17_7579313-7579313_T_CSubstitution No Yes 19.98% CGCRC333 chr17_7577610-7577610_A_TSubstitution No Yes 43.03% CGCRC333 chr7_140453136-140453136_T_GSubstitution Yes Yes 22.26% CGCRC333 chr2_212495194-212495194_C_TSubstitution No No 1.00% CGCRC334 chr17_7577548-7577548_C_T SubstitutionYes Yes 13.44% CGCRC334 chr7_55238900-55238900_C_T Substitution NA Yes35.28% CGCRC334 chr3_178916924-178916924_C_G Substitution No No 3.85%CGCRC335 chr7_140453136-140453136_A_T Substitution Yes Yes 0.32%CGCRC336 chr17_7578406-7578406_C_T Substitution Yes Yes 75.76% CGCRC336chr12_25398284-25398284_C_A Substitution Yes Yes 42.87% CGCRC336chr5_112175147-112175147_G_T Substitution No Yes 81.61% CGCRC337chr19_1220718-1220718_T_A Substitution No No 0.12% CGCRC337chr5_112162851-112162851_G_A Substitution NA Yes 46.26% OGORC338chr12_25398284-25398284_C_T Substitution Yes Yes 27.03% CGCRC339chr12_25398281-25398281_C_T Substitution Yes Yes 1.94% CGCRC339chr5_112173917-112173917_C_T Substitution Yes Yes 2.35% CGCRC339chr3_178927457-178927457_G_T Substitution No Yes 3.14% CGCRC339chr3_178952085-178952085_A_T Substitution Yes Yes 1.71% CGCRC340chr17_7578263-7578263_G_A Substitution Yes Yes 18.26% CGCRC340chr5_112175207-112175207_G_T Substitution Yes Yes 22.57% CGPLBR38chr17_7577560-7577560_A_G Substitution No Yes 0.53% CGPLBR40chrX_66766163-66766163_C_G Substitution NA Yes 28.99% CGPLBR44chr2_25457242-25457242_C_T Substitution Yes Yes 1.82% CGPLBR44chr2_25463568-25463568_A_G Substitution No Yes 0.41% CGPLBR44chr4_55153609-55153609_G_A Substitution No Yes 0.13% CGPLBR48chr2_2936301-2936301_C_T Substitution NA Yes 34.61% CGPLBR48chr7_55240762-55240762_G_A Substitution No No 0.18% CGPLBR55chr2_25463266-25463266_G_A Substitution No No 0.18% CGPLBR55chr20_57484421-57484421_G_A Substitution Yes Yes 0.68% CGPLBR55chr_178921553-178921553_T_A Substitution Yes Yes 0.42% CGPLBR63chr3_1806188-1806188_A_G Substitution NA Yes 34.82% CGPLBR67chr4_25457242-25457242_C_T Substitution Yes Yes 0.11% CGPLBR67chr3_178936091-178936091_G_A Substitution Yes Yes 0.68% CGPLBR67chr2_212285302-212285302_T_G Substitution No No 0.28% CGPLBR69chr2_25463172-25463172_T_A Substitution No No 0.29% CGPLBR69chr3_41266092-41266092_A_C Substitution NA Yes 41.74% CGPLBR69chr2_209108158-209108158_A_T Substitution NA Yes 41.86% CGPLBR70chr11_108216546-108216546_G_A Substitution No No 0.36% CGPLBR70chr5_112176022-112176022_A_C Substitution NA Yes 40.28% CGPLBR71chr17_7577120-7577120_C_T Substitution Yes Yes 0.10% CGPLBR72chr5_112175886-112175886_A_G Substitution NA Yes 44.03% CGPLBR73chr2_29474053-29474053_A_G Substitution No No 0.27% CGPLBR73chr2_212652833-212652833_G_T Substitution NA Yes 35.58% CGPLBR74chrX_66788865-66788865_G_T Substitution NA Yes 36.23% CGPLBR75chr3_178952085-178952085_A_G Substitution Yes Yes 0.14% CGPLBR76chr4_55946310-55946310_C_T Substitution NA Yes 36.57% CGPLBR76chr3_178952085-178952085_A_G Substitution Yes Yes 0.12% CGPLBR77chr10_89711891-89711891_G_T Substitution No Yes 2.29% CGPLBR80chr9_21974792-21974792_G_A Substitution No No 0.54% CGPLBR83chrX_66937328-66937328_A_G Substitution NA Yes 42.66% CGPLBR83chr11_108117753-108117753_G_A Substitution No No 0.28% CGPLBR83chr2_212543783-212543783_T_G Substitution NA Yes 44.91% CGPLBR86chr19_1223125-1223125_C_G Substitution NA Yes 42.32% Wild-type Fragments25th Minimum Percentile Mode Median cfDNA cfDNA cfDNA cfDNA FragmentFragment Fragment Fragment Distinct Size Size Size Size Patient Coverage(bp) (bp) (bp) (bp) CGCRC316 12880 100 150 166 163 CGCRC316 7479 93 157164 168 CGCRC316 13682 100 149 165 162 CGCRC316 16716 85 153 166 156CGCRC316 17060 100 150 166 153 CGCRC317 14587 84 152 166 154 CGCRC31710483 100 152 164 155 CGCRC317 3497 101 149 166 163 CGCRC318 16436 98158 170 170 CGCRC320 6521 100 163 170 175 CGCRC320 11633 100 162 174 174CGCRC321 6918 88 161 167 174 CGCRC321 9559 94 159 171 170 CGCRC321 5545100 159 172 172 CGCRC332 605 104 164 170 176 CGCRC333 1265 89 159 165171 CGCRC333 3338 102 153 165 169 CGCRC333 3008 102 153 169 109 CGCRC3341725 105 160 170 175 CGCRC334 1168 100 159 164 174 CGCRC334 1798 103 159166 173 CGCRC335 2411 99 155 167 167 CGCRC336 757 104 156 171 170CGCRC336 1080 102 150 166 167 CGCRC336 391 102 161 165 171 CGCRC337 649772 153 169 177 CGCRC337 1686 100 147 170 153 OGORC338 1408 105 153 164156 CGCRC339 1256 105 158 168 159 CGCRC339 1639 101 158 165 172 CGCRC3391143 100 154 170 167 CGCRC339 1584 108 161 171 173 CGCRC340 876 101 162170 175 CGCRC340 796 105 159 164 174 CGPLBR38 9684 95 156 166 168CGPLBR40 10277 78 162 168 173 CGPLBR44 10715 99 162 171 173 CGPLBR4410837 100 159 169 171 CGPLBR44 12640 100 159 168 171 CGPLBR48 5631 100164 170 179 CGPLBR48 12467 101 167 174 180 CGPLBR55 10527 101 158 169169 CGPLBR55 6011 101 153 166 167 CGPLBR55 3973 101 153 166 166 CGPLBR633405 97 165 170 176 CGPLBR67 10259 87 157 166 168 CGPLBR67 5163 100 151167 165 CGPLBR67 6250 100 155 166 187 CGPLBR69 7558 100 159 166 170CGPLBR69 3938 101 154 169 166 CGPLBR69 2387 101 157 166 168 CGPLBR706916 100 158 171 169 CGPLBR70 3580 107 160 169 173 CGPLBR71 7930 85 156166 158 CGPLBR72 2389 100 157 160 170 CGPLBR73 11348 95 161 173 174CGPLBR73 3422 102 157 168 169 CGPLBR74 9784 101 163 175 174 CGPLBR757290 103 162 173 172 CGPLBR76 4342 104 166 171 179 CGPLBR76 11785 100165 168 177 CGPLBR77 6161 100 158 166 169 CGPLBR80 3643 96 166 166 185CGPLBR83 3479 105 162 164 174 CGPLBR83 3496 103 165 170 177 CGPLBR831748 100 164 173 175 CGPLBR86 4241 98 160 168 175 Stage at Amino AcidPatient Patient Type Diagnosis Alteration Type Gene (Protein) CGPLBR86Breast Cancer II Germline SMARCB1 795 + 3A > G CGPLBR87 Breast Cancer IITumor-derived JAK2 215R > X CGPLBR87 Breast Cancer II HematopoieticDNMT3A 882R > H CGPLBR87 Breast Cancer II Tumor-derived SMAD4 496R > CCGPLBR87 Breast Cancer II Germline AR 651S > N CGPLBR88 Breast Cancer IITumor-derived CDK6 51E > K CGPLBR88 Breast Cancer II Germline APC1125V > A CGPLBR92 Breast Cancer II Tumor-derived TP53 257L > P CGPLBR96Breast Cancer II Tumor-derived TP53 213R > X CGPLBR96 Breast Cancer IIHematopoietic DNMT3A 531D > G CGPLBR96 Breast Cancer II Tumor-derived AR13R > Q CGPLBR97 Breast Cancer II Hematopoietic DNMT3A 882R > H CGPLBR97Breast Cancer II Germline PDGFRA 401A > D CGPLBR97 Breast Cancer IITumor-derived GNAS 201R > H CGPLLU144 Lung Cancer II Tumor-derived TP53241S > F CGPLLU144 Lung Cancer II Tumor-derived KRAS 12G > C CGPLLU144Lung Cancer II Tumor-derived EGFR 373P > S CGPLLU144 Lung Cancer IITumor-derived ATM 292P > L CGPLLU144 Lung Cancer II Tumor-derived PIK3CA545E > K CGPLLU144 Lung Cancer II Tumor-derived ERBB4 426R > K CGPLLU146Lung Cancer II Tumor-derived JAK2 617V > F CGPLLU146 Lung Cancer IITumor-derived TP53 282R > P CGPLLU146 Lung Cancer II Tumor-derivedDNMT3A 737L > H CGPLLU146 Lung Cancer II Tumor-derived RB1 861 + 2T > CCGPLLU146 Lung Cancer II Tumor-derived ATM 581L > F CGPLLU147 LungCancer III Tumor-derived TP53 248R > Q CGPLLU147 Lung Cancer IIITumor-derived TP53 201L > X CGPLLU147 Lung Cancer III Tumor-derived ALK1537G > E CGPLLU147 Lung Cancer III Germline PDGFRA 200T > S CGPLLU162Lung Cancer II Tumor-derived CDKN2A 12S > L CGPLLU162 Lung Cancer IITumor-derived EGFR 858L > R CGPLLU162 Lung Cancer II Tumor-derived BRAF354R > Q CGPLLU163 Lung Cancer II Tumor-derived CDKN2A 12S > L CGPLLU163Lung Cancer II Hematopoietic DNMT3A 528Y > D CGPLLU164 Lung Cancer IITumor-derived STK11 216S > Y CGPLLU164 Lung Cancer II Germline STK11354F > L CGPLLU164 Lung Cancer II Tumor-derived GNA11 606 − 3C > TCGPLLU164 Lung Cancer II Tumor-derived TP53 278P > S CGPLLU164 LungCancer II Tumor-derived TP53 161A > S CGPLLU164 Lung Cancer IITumor-derived TP53 160M > I CGPLLU164 Lung Cancer II Tumor-derived ERBB41299P > L CGPLLU164 Lung Cancer II Tumor-derived ERBB4 253N > SCGPLLU165 Lung Cancer II Tumor-derived STK11 354F > L CGPLLU165 LungCancer I Tumor-derived GNAS 201R > H CGPLLU168 Lung Cancer ITumor-derived TP53 136Q > X CGPLLU168 Lung Cancer I Hematopoietic DNMT3A736R > S CGPLLU168 Lung Cancer I Tumor-derived EGFR 858L > R CGPLLU174Lung Cancer I Tumor-derived STK11 597 + 1G > T CGPLLU174 Lung Cancer ITumor-derived JAK2 160D > Y CGPLLU174 Lung Cancer I Tumor-derived KRAS12G > C CGPLLU174 Lung Cancer I Hematopoietic DNMT3A 891R > W CGPLLU174Lung Cancer I Hematopoietic DNMT3A 715I > M CGPLLU175 Lung Cancer ITumor-derived TP53 179H > R CGPLLU175 Lung Cancer I Hematopoietic DNMT3A2598 − 1I > A CGPLLU175 Lung Cancer I Hematopoietic DNMT3A 755F > LCGPLLU175 Lung Cancer I Germline ATM 337R > C CGPLLU175 Lung Cancer ITumor-derived ERBB4 941Q > X CGPLLU176 Lung Cancer I HematopoieticDNMT3A 750P > S CGPLLU176 Lung Cancer I Hematopoietic DNMT3A 735Y > CCGPLLU177 Lung Cancer II Tumor-derived KRAS 12G > V CGPLLU177 LungCancer II Hematopoietic DNMT3A 897V > G CGPLLU177 Lung Cancer IIHematopoietic DNMT3A 862R > C CGPLLU177 Lung Cancer II HematopoieticDNMT3A 2173 + 1 > A CGPLLU178 Lung Cancer I Tumor-derived CDH1 251 > MCGPLLU178 Lung Cancer I Tumor-derived PIK3CA 861Q > X CGPLLU179 LungCancer I Hematopoietic DNMT3A 879N > D CGPLLU179 Lung Cancer I GermlineAPC 2611T > I Alteration Mutant Mutation Hotspot Detected Allele PatientNucleotide Type Alteration in Tissue Fraction CGPLBR86chr22_24159126-24159124_A_G Substitution NA Yes 42.38% CGPLBR87chr9_5054591-5054591_C_T Substitution No No 0.35% CGPLBR87chr2_25457242-25457242_C_T Substitution You No 0.31% CGPLBR87chr18_48604664-48604664_C_T Substitution No No 0.40% CGPLBR87chrX_66931310-66931310_G_A Substitution NA Yes 42.94% CGPLBR88chr7_92462487-92462487_C_T Substitution No No 0.13% CGPLBR88chr5_112174665-112174665_T_C Substitution NA Yes 31.19% CGPLBR92chr17_7577511-7577511_A_G Substitution No Yes 0.20% CGPLBR96chr17.fa:7578212-7578212_G_A Substitution Yes No 0.10% CGPLBR96chr2_25467484-25467484_C_T Substitution No Yes 5.81% CGPLBR96chrX_66765026-66765026_G_A Substitution No No 0.60% CGPLBR97chr2_25457242-25457242_C_T Substitution Yes Yes 0.11% CGPLBR97chr4_55136880-55136880_C_A Substitution NA Yes 34.12% CGPLBR97chr20_57484421-57484421_G_A Substitution Yes Yes 0.13% CGPLLU144chr17_7577559-7577559_G_A Substitution Yes Yes 1.95% CGPLLU144chr12_25398285-25398285_C_A Substitution Yes Yes 5.10% CGPLLU144chr7_55224336-55224336_C_T Substitution No Yes 0.16% CGPLLU144chr11_108115727-108115727_C_T Substitution No No 0.22% CGPLLU144chr3_178936091-178936091_G_A Substitution Yes Yes 2.94% CGPLLU144chr2_212568841-212568841_C_T Substitution No No 0.18% CGPLLU146chr9_5073770-5073770_G_T Substitution Yes No 0.25% CGPLLU146chr17_7577093-7577093_C_G Substitution No Yes 1.30% CGPLLU146chr2_25463283-25463283_A_T Substitution No Yes 0.84% CGPLLU146chr13_48937095-48937095_T_C Substitution No Yes 0.87% CGPLLU146chr11_108122699-108122699_A_T Substitution No No 0.20% CGPLLU147chr17_7577538-7577538_C_T Substitution Yes No 0.15% CGPLLU147chr17_7578247-7578247_A_T Substitution No Yes 0.55% CGPLLU147chr2_29416343-29416343_C_T Substitution No Yes 0.94% CGPLLU147chr4_55130065-55130065_C_G Substitution NA Yes 43.47% CGPLLU162chr9_21974792-21974792_G_A Substitution No No 0.22% CGPLLU162chr7_55259515-55259515_T_G Substitution Yes Yes 0.22% CGPLLU162chr7_140494187-140494187_C_T Substitution No No 0.14% CGPLLU163chr9_21974792-21974792_G_A Substitution No No 0.21% CGPLLU163chr2_25467494-25467494_A_C Substitution No Yes 0.15% CGPLLU164chr19_1220629-1220629_C_A Substitution No Yes 1.23% CGPLLU164chr19_1223125-1223125_C_G Substitution NA Yes 45.52% CGPLLU164chr19_3118919-3118919_C_T Substitution No No 0.20% CGPLLU164chr17_7577106-7577106_G_A Substitution Yes No 0.10% CGPLLU164chr17_7578449-7578449_C_A Substitution No Yes 1.78% CGPLLU164chr17_7578450-7578450_C_A Substitution No Yes 1.86% CGPLLU164chr2_212248371-212248371_G_A Substitution No Yes 0.96% CGPLLU164chr2_212587243-212587243_T_C Substitution No No 0.22% CGPLLU165chr19_1223125-1223125_C_G Substitution NA Yes 36.62% CGPLLU165chr20_57484421-57484421_G_A Substitution Yes Yes 0.16% CGPLLU168chr17.fa:7578524-7578524_G_A Substitution Yes Yes 0.06% CGPLLU168chr2_25463287-25463287_G_T Substitution No No 0.39% CGPLLU168chr7.fa:55259515-55259515_T_G Substitution Yes Yes 0.07% CGPLLU174chr19_1220505-1220505_G_T Substitution No Yes 0.33% CGPLLU174chr9_5050695-5050695_G_T Substitution No Yes 0.40% CGPLLU174chr12_25398285-25398285_C_A Substitution Yes Yes 0.16% CGPLLU174chr2_25457216-25457216_G_A Substitution No Yes 0.29% CGPLLU174chr2_25463537-25463537_G_C Substitution No Yes 0.26% CGPLLU175chr17_7578394-7578394_T_C Substitution Yes Yes 8.03% CGPLLU175chr2_25457216-25457216_C_T Substitution No No 0.21% CGPLLU175chr2_25463230-25463230_A_G Substitution No No 0.15% CGPLLU175chr11_108117798-108117798_C_T Substitution NA Yes 43.84% CGPLLU175chr2_212288925-212288925_G_A Substitution No Yes 3.64% CGPLLU176chr2_25463245-25463245_G_A Substitution No Yes 0.92% CGPLLU176chr2_25463289-25463289_T_C Substitution No Yes 0.12% CGPLLU177chr12_25398284-25398284_C_A Substitution Yes Yes 2.49% CGPLLU177chr2_25457197-25457197_A_C Substitution No Yes 1.53% CGPLLU177chr2_25457243-25457243_G_A Substitution Yes No 0.29% CGPLLU177chr2_25463508-25463508_C_T Substitution No No 0.13% CGPLLU178chr16_68844164-68844164_C_T Substitution No No 0.29% CGPLLU178chr3_178947145-178947145_C_T Substitution No No 0.17% CGPLLU179chr2_25457252-25457252_T_C Substitution No Yes 0.38% CGPLLU179chr5_112179123-112179123_C_T Substitution NA Yes 39.91% Wild-typeFragments 25th Minimum Percentile Mode Median cfDNA cfDNA cfDNA cfDNAFragment Fragment Fragment Fragment Distinct Size Size Size Size PatientCoverage (bp) (bp) (bp) (bp) CGPLBR86 3096 88 160 167 174 CGPLBR87 3680101 162 168 175 CGPLBR87 6180 101 163 164 175 CGPLBR87 7746 86 160 167175 CGPLBR87 2286 106 160 166 172 CGPLBR88 17537 89 185 200 223 CGPLBR885919 101 162 172 173 CGPLBR92 15530 77 150 164 152 CGPLBR96 9893 100 159164 171 CGPLBR96 8620 95 162 167 173 CGPLBR96 8036 85 162 169 175CGPLBR97 14856 93 160 168 170 CGPLBR97 5329 100 161 165 171 CGPLBR977010 97 158 169 170 CGPLLU144 11371 100 156 165 167 CGPLLU144 7641 100155 167 166 CGPLLU144 9996 100 158 168 169 CGPLLU144 4956 101 159 166169 CGPLLU144 6540 100 153 170 168 CGPLLU144 7648 101 156 164 166CGPLLU146 5920 100 155 164 168 CGPLLU146 9356 100 155 166 168 CGPLLU1467284 101 158 165 170 CGPLLU146 4183 103 160 166 170 CGPLLU146 6778 100157 166 158 CGPLLU147 4807 100 155 166 170 CGPLLU147 5282 100 156 167171 CGPLLU147 7122 100 158 174 173 CGPLLU147 2825 101 160 165 173CGPLLU162 9940 95 161 164 174 CGPLLU162 13855 87 160 174 173 CGPLLU16211251 100 153 167 165 CGPLLU163 10805 85 159 165 173 CGPLLU163 20185 83158 166 170 CGPLLU164 8795 91 156 161 169 CGPLLU164 4561 92 157 164 169CGPLLU164 8097 100 158 170 170 CGPLLU164 9241 100 155 165 157 CGPLLU16410806 100 157 168 159 CGPLLU164 10919 100 157 168 159 CGPLLU164 5412 103159 175 170 CGPLLU164 5151 101 160 166 169 CGPLLU165 7448 95 155 167 167CGPLLU165 5822 102 154 166 166 CGPLLU168 15985 97 152 165 166 CGPLLU16811070 100 156 165 168 CGPLLU168 11063 83 157 166 169 CGPLLU174 5881 88162 165 174 CGPLLU174 3696 100 162 167 172 CGPLLU174 4941 101 162 167172 CGPLLU174 7527 100 163 168 173 CGPLLU174 8353 101 162 168 173CGPLLU175 10214 100 160 166 170 CGPLLU175 9739 100 157 168 158 CGPLLU1759509 100 157 165 158 CGPLLU175 2710 101 157 165 157 CGPLLU175 6565 100158 166 158 CGPLLU176 6513 101 164 168 175 CGPLLU176 5962 100 164 174175 CGPLLU177 7044 102 160 165 170 CGPLLU177 9950 88 160 169 171CGPLLU177 11233 100 160 168 171 CGPLLU177 10966 75 160 169 172 CGPLLU1785378 100 162 176 172 CGPLLU178 7235 101 159 167 170 CGPLLU179 6350 103161 169 171 CGPLLU179 2609 108 162 171 173 Stage at Amino Acid PatientPatient Type Diagnosis Alteration Type Gene (Protein) CGPLLU180 LungCancer I Tumor-derived STK11 237D > Y CGPLLU180 Lung Cancer ITumor-derived TP53 293G > V CGPLLU180 Lung Cancer I Tumor-derived TP53282R > P CGPLLU180 Lung Cancer I Tumor-derived TP53 177P > L CGPLLU180Lung Cancer I Tumor-derived RB1 565S > X CGPLLU197 Lung Cancer IHematopoietic DNMT3A 882R > C CGPLLU197 Lung Cancer I HematopoieticDNMT3A 879N > D CGPLLU198 Lung Cancer I Tumor-derived TP53 162I > NCGPLLU198 Lung Cancer I Tumor-derived EGFR 858L > R CGPLLU202 LungCancer I Tumor-derived EGFR 790T > M CGPLLU202 Lung Cancer ITumor-derived EGFR 868E > X CGPLLU204 Lung Cancer I Tumor-derived KIT956R > Q CGPLLU205 Lung Cancer II Hematopoietic DNMT3A 736R > CCGPLLU205 Lung Cancer II Hematopoietic DNMT3A 696Q > X CGPLLU206 LungCancer III Tumor-derived TP53 672 + 1G > A CGPLLU206 Lung Cancer IIITumor-derived TP53 131N > S CGPLLU207 Lung Cancer II Tumor-derived TP53376 − 1G > A CGPLLU207 Lung Cancer II Germline ALK 419P > L CGPLLU207Lung Cancer II Tumor-derived EGFR 790T > M CGPLLU208 Lung Cancer IITumor-derived TP53 250P > L CGPLLU208 Lung Cancer II Germline EGFR224R > H CGPLLU208 Lung Cancer II Tumor-derived EGFR 858L > R CGPLLU208Lung Cancer II Tumor-derived MYC 98R > W CGPLLU209 Lung Cancer IIGermline STK11 354F > L CGPLLU209 Lung Cancer II Tumor-derived TP53100Q > X CGPLLU209 Lung Cancer II Tumor-derived CDKN2A 88E > X CGPLLU209Lung Cancer II Tumor-derived PDGFRA 921A > T CGPLLU209 Lung Cancer IIGermline EGFR 567M > V CGPLOV10 Ovarian Cancer I Tumor-derived TP53342R > X CGPLOV11 Ovarian Cancer IV Tumor-derived TP53 248R > Q CGPLOV11Ovarian Cancer IV Germline TP53 63A > V CGPLOV13 Ovarian Cancer IVTumor-derived ALK 444W > C CGPLOV13 Ovarian Cancer IV Germline PDGFRA401A > D CGPLOV13 Ovarian Cancer IV Tumor-derived KIT 135R > H CGPLOV14Ovarian Cancer I Tumor-derived HNF1A 230E > K CGPLOV15 Ovarian CancerIII Tumor-derived TP53 278P > S CGPLOV15 Ovarian Cancer IIITumor-derived EGFR 433H > D CGPLOV17 Ovarian Cancer I Tumor-derived TP53248R > Q CGPLOV17 Ovarian Cancer I Germline PDGFRA 1071D > N CGPLOV18Ovarian Cancer I Germline APC 1125V > A CGPLOV19 Ovarian Cancer IIGermline FGFR3 403K > E CGPLOV19 Ovarian Cancer II Tumor-derived TP53273R > H CGPLOV19 Ovarian Cancer II Germline AR 176S > R CGPLOV19Ovarian Cancer II Tumor-derived APC 1378Q > X CGPLOV20 Ovarian Cancer IITumor-derived TP53 195I > T CGPLOV20 Ovarian Cancer II Germline EGFR253K > R CGPLOV21 Ovarian Cancer IV Germline STK11 354F > L CGPLOV21Ovarian Cancer IV Tumor-derived TP53 275C > Y CGPLOV21 Ovarian Cancer IVTumor-derived ERBB4 602S > T CGPLOV22 Ovarian Cancer III Tumor-derivedTP53 193H > P CGPLOV22 Ovarian Cancer III Tumor-derived CTNNB1 41T > AAlteration Mutant Mutation Hotspot Detected Allele Patient NucleotideType Alteration in Tissue Fraction CGPLLU180 chr19_1220691-1220691_G_TSubstitution No You 2.43% CGPLLU180 chr17_7577060-7577060_C_ASubstitution No Yes 2.07% CGPLLU180 chr17_7577093-7577093_C_GSubstitution No Yes 1.94% CGPLLU180 chr17:fa_7578400-7578400_G_ASubstitution Yes No 0.08% CGPLLU180 chr13_48955578-48955578_C_GSubstitution No Yes 1.01% CGPLLU197 chr2_25457243-25457243_G_ASubstitution Yes No 0.16% CGPLLU197 chr2_25457252-25457252_T_CSubstitution No No 0.38% CGPLLU198 chr17_7578445-7578445_A_TSubstitution No Yes 0.87% CGPLLU198 chr7_55259515-55259515_T_GSubstitution Yes Yes 0.52% CGPLLU202 chr7:fa_55249071-55249071_C_TSubstitution Yes Yes 0.05% CGPLLU202 chr7_55259544-55259544_G_TSubstitution No No 0.13% CGPLLU204 chr4_55604659-55604659_G_ASubstitution No No 0.26% CGPLLU205 chr2_25463287-25463287_G_ASubstitution No Yes 0.70% CGPLLU205 chr2_25463598-25463598_G_ASubstitution No Yes 3.47% CGPLLU206 chr17_7578176-7578176_C_TSubstitution Yes Yes 26.13% CGPLLU206 chr17_7578538-7578538_T_CSubstitution No No 0.21% CGPLLU207 chr17_7578555-7578555_C_TSubstitution Yes Yes 0.32% CGPLLU207 chr2_29606625-29606625_A_GSubstitution NA Yes 34.38% CGPLLU207 chr7:fa_55249071-55249071_C_TSubstitution Yes No 0.09% CGPLLU208 chr17_7577532-7577532_G_ASubstitution Yes Yes 1.33% CGPLLU208 chr7_55220281-55220281_G_ASubstitution NA Yes 39.34% CGPLLU208 chr7_55259515-55259515_T_GSubstitution Yes Yes 0.86% CGPLLU208 chr8_128750755-128750755_C_TSubstitution No No 0.17% CGPLLU209 chr19_1223125-1223125_C_GSubstitution NA Yes 26.84% CGPLLU209 chr17_7579389-7579389_G_ASubstitution No Yes 9.97% CGPLLU209 chr9_21971096-21971096_C_ASubstitution Yes Yes 9.13% CGPLLU209 chr4_55155052-55155052_G_ASubstitution No Yes 9.82% CGPLLU209 chr7_55231493-55231493_A_GSubstitution NA Yes 30.41% CGPLOV10 chr17_7574003-7574003_G_ASubstitution Yes Yes 3.14% CGPLOV11 chr17_7577538-7577538_C_TSubstitution Yes Yes 0.87% CGPLOV11 chr17_7579499-7579499_G_ASubstitution NA Yes 37.77% CGPLOV13 chr2_29551296-29551296_C_ASubstitution No Yes 0.12% CGPLOV13 chr4_55136880-55136880_C_ASubstitution NA Yes 37.98% CGPLOV13 chr4_55564516-55564516_G_ASubstitution No Yes 0.35% CGPLOV14 chr12_121431484-121431484_G_ASubstitution No No 0.14% CGPLOV15 chr17_7577106-7577106_G_A SubstitutionYes Yes 3.54% CGPLOV15 chr7_55225445-55225445_C_G Substitution No No0.19% CGPLOV17 chr17_7577538-7577538_C_T Substitution Yes Yes 0.32%CGPLOV17 chr4_55161382-55161382_G_A Substitution NA Yes 44.10% CGPLOV18chr5_112174665-112174665_T_C Substitution NA Yes 40.81% CGPLOV19chr4_1806186-1806186_A_G Substitution NA Yes 23.80% CGPLOV19chr17_7577120-7577120_C_T Substitution Yes Yes 36.83% CGPLOV19chrX_66765516-66765516_C_A Substitution NA Yes 65.29% CGPLOV19chr5_112175423-112175423_C_T Substitution Yes Yes 46.35% CGPLOV20chr17_7578265-7578265_A_G Substitution Yes Yes 0.21% CGPLOV20chr7_55221714-55221714_A_G Substitution NA Yes 44.05% CGPLOV21chr19_1223125-1223125_C_G Substitution NA Yes 7.68% CGPLOV21chr17_7577114-7577114_C_T Substitution No Yes 2.04% CGPLOV21chr2_212530114-212530114_C_G Substitution No No 14.36% CGPLOV22chr17_7578271-7578271_T_G Substitution No Yes 0.49% CGPLOV22chr3_41266124-41266124_A_G Substitution Yes Yes 0.34% Wild-typeFragments 25th Minimum Percentile Mode Median cfDNA cfDNA cfDNA cfDNAFragment Fragment Fragment Fragment Distinct Size Size Size Size PatientCoverage (bp) (bp) (bp) (bp) CGPLLU180 6065 91 158 165 170 CGPLLU1806680 92 158 164 169 CGPLLU180 7790 92 158 167 168 CGPLLU180 9036 101 160169 171 CGPLLU180 4679 100 157 169 158 CGPLLU197 7196 102 162 166 172CGPLLU197 7147 100 161 166 172 CGPLLU198 9322 97 157 165 158 CGPLLU1988303 100 160 173 172 CGPLLU202 14197 90 151 165 166 CGPLLU202 9279 51150 168 167 CGPLLU204 7185 100 157 165 168 CGPLLU205 10739 96 156 165166 CGPLLU205 12065 100 154 165 165 CGPLLU206 6746 94 148 165 164CGPLLU206 11225 100 147 167 164 CGPLLU207 11224 100 159 165 170CGPLLU207 4960 101 160 166 170 CGPLLU207 13216 85 161 165 172 CGPLLU2089211 101 156 166 168 CGPLLU208 5253 100 159 164 170 CGPLLU208 10733 100160 170 171 CGPLLU208 11421 100 158 165 171 CGPLLU209 11695 96 153 166159 CGPLLU209 12771 94 155 163 168 CGPLLU209 16557 92 157 169 170CGPLLU209 13057 97 158 167 171 CGPLLU209 8521 100 155 167 169 CGPLOV104421 101 161 165 172 CGPLOV11 7987 100 157 164 169 CGPLOV11 3782 97 160166 171 CGPLOV13 12072 88 157 165 169 CGPLOV13 4107 103 159 166 169CGPLOV13 6427 100 161 165 171 CGPLOV14 11418 92 154 166 171 CGPLOV157689 102 157 164 169 CGPLOV15 7617 101 159 167 171 CGPLOV17 4463 96 156168 169 CGPLOV17 2884 110 157 170 170 CGPLOV18 2945 101 159 164 169CGPLOV19 9727 95 158 167 172 CGPLOV19 4387 100 158 165 169 CGPLOV19 277593 161 171 171 CGPLOV19 3616 102 156 170 170 CGPLOV20 5404 94 159 165170 CGPLOV20 3744 102 158 166 169 CGPLOV21 21823 81 158 166 169 CGPLOV2118806 101 159 165 169 CGPLOV21 10801 89 160 166 169 CGPLOV22 11952 100155 165 167 CGPLOV22 12399 92 150 165 164 Mutant Fragments 75th 25thMean Percentile Maximum Minimum Percentile cfDNA cfDNA cfDNA cfDNA cfDNAFragment Fragment Fragment Fragment Fragment Size Size Size DistinctSize Size (bp) (bp) (bp) Coverage (bp) (bp) 179 186 400 19 100 142 182185 400 21 132 166 180 183 400 5411 92 152 177 182 400 1903 100 148 184185 400 1344 108 155 181 182 400 2108 100 153 176 180 400 1951 101 149176 183 399 75 123 162 177 182 400 28 101 130 183 188 399 6863 100 160188 186 400 34 77 154 175 179 396 9 138 147 184 185 400 21 115 145 179185 397 30 137 149 179 182 397 44 125 155 185 186 400 8167 101 180 187186 400 3552 102 158 184 187 399 15 93 137 183 185 400 26 137 163 181182 397 35 118 147 172 175 400 71 133 152 169 174 400 55 130 153 189 187390 17 149 155 176 183 400 18 156 170 169 175 397 51 108 143 166 173 39726 118 147 184 186 400 45 116 151 185 186 400 25 157 165 185 187 400 25124 168 167 175 394 86 121 155 167 173 397 45 124 143 170 175 396 108126 147 190 189 400 23 131 148 182 182 399 42 138 155 189 187 399 25 126153 192 193 400 977 101 149 173 179 391 525 102 140 181 185 399 4010 100158 178 184 399 625 100 140 175 179 398 37 111 143 181 186 398 3184 102159 180 183 399 47 111 148 183 184 397 39 111 146 185 184 400 24 110 146176 180 400 32 117 146 180 184 399 43 111 143 185 187 400 29 109 140 179182 399 20 128 152 176 184 396 7515 101 160 182 182 399 31 85 145 181182 395 428 100 135 176 180 397 352 97 136 165 172 397 15 131 137 170173 398 25 107 138 171 173 400 27 122 147 189 169 400 91 112 165 189 169400 27 124 144 178 184 399 24 105 143 188 189 399 8 122 143 194 192 40017 144 163 180 183 394 15 132 159 183 185 399 233 131 162 186 186 398 27136 155 192 195 399 23 137 144 182 184 399 29 131 157 DifferenceDifference Adjusted P between between Value of Median Mean DifferenceMutant Fragments Mutant Mutant between 75th and and Mutant Mode MedianMean Percentile Maximum Wild type Wild-type and cfDNA cfDNA cfDNA cfDNAcfDNA cfDNA cfDNA Wild-type Fragment Fragment Fragment Fragment FragmentFragment Fragment cfDNA Size Size Size Size Size Size Size Fragment (bp)(bp) (bp) (bp) (bp) (bp) (bp) Size 233 165 180 230 305 −4.0 1.54 0.475182 176 191 198 309 7.0 8.33 0.250 167 169 186 191 399 0.0 5.89 0.000166 166 177 183 383 −1.0 −0.25 0.874 167 170 189 191 398 1.0 5.37 0.009166 168 185 187 386 1.0 3.80 0.025 175 167 179 182 397 0.0 2.65 0.148167 172 182 190 370 3.0 5.31 0.368 130 139 164 155 345 −29.5 −12.790.000 165 173 185 159 400 2.0 3.13 0.002 171 170 177 192 335 −0.5 −11.460.571 176 171 177 176 290 4.0 1.22 0.475 155 159 176 175 368 −11.0 −7.990.052 181 162 182 161 369 −8.0 3.49 0.061 155 169 185 194 338 0.0 5.780.623 166 171 184 187 400 −1.0 −1.27 0.212 168 170 185 185 399 0.0 −2.620.114 127 174 173 193 261 3.0 −11.00 0.507 166 167 179 180 364 −3.0−4.34 0.430 176 163 172 176 336 −6.0 −9.35 0.166 170 165 169 173 301 0.03.57 0.668 165 164 166 166 325 0.0 −2.15 0.630 326 170 221 301 387 −3.032.43 0.453 174 174 210 219 372 5.0 33.84 0.368 268 152 164 176 268−12.0 −5.12 0.000 153 156 174 158 327 −9.5 8.37 0.036 168 163 175 177346 −8.0 −8.84 0.057 191 175 207 199 350 3.0 22.93 0.456 180 180 189 191338 8.0 4.06 0.154 169 166 168 175 309 2.0 0.46 0.445 197 162 166 168377 −1.0 −0.91 0.482 162 162 164 174 302 −3.0 −6.74 0.064 145 166 189205 333 −5.0 −0.80 0.297 155 174 177 187 343 5.5 −4.51 0.171 176 176 188229 305 7.0 −0.19 0.234 189 170 182 192 380 −1.0 −9.76 0.000 168 159 168176 382 −7.0 −5.57 0.052 166 170 181 185 398 0.0 0.37 0.770 167 162 172181 380 −9.0 −6.68 0.009 142 166 172 186 321 −1.0 −2.36 0.572 168 172182 187 400 0.5 0.95 0.564 144 169 176 153 353 −1.0 −4.83 0.598 182 162182 155 337 −7.0 −0.44 0.064 309 182 208 284 355 14.0 22.31 0.031 154157 167 166 298 −11.0 −8.94 0.013 144 177 187 212 319 9.0 7.22 0.062 204159 186 204 387 −12.0 3.32 0.031 180 163 166 180 219 −6.5 −13.04 0.155170 171 177 185 400 1.0 1.08 0.166 137 166 167 176 316 −3.0 −14.62 0.469138 149 158 166 340 −20.0 −23.47 0.000 132 147 149 159 326 21.0 26.040.000 132 144 163 171 323 −20.0 −1.73 0.000 159 161 175 190 299 −3.04.83 0.384 161 161 173 171 342 −3.0 2.54 0.354 168 173 196 192 397 1.06.83 0.571 154 154 167 172 320 −19.0 −22.39 0.000 132 159 183 190 367−11.0 4.67 0.054 122 161 168 195 241 −13.0 −19.21 0.100 173 173 213 261372 1.0 19.22 0.587 186 166 174 185 265 −3.0 −5.62 0.461 167 172 190 187394 2.0 7.27 0.137 183 163 170 178 262 −7.0 −16.03 0.131 175 152 190 212327 −17.0 −1.78 0.018 177 171 183 179 319 −1.0 −0.74 0.564 MutantFragments 75th 25th Mean Percentile Maximum Minimum Percentile cfDNAcfDNA cfDNA cfDNA cfDNA Fragment Fragment Fragment Fragment FragmentSize Size Size Distinct Size Size (bp) (bp) (bp) Coverage (bp) (bp) 166172 396 1616 100 146 175 180 400 806 96 158 165 172 399 1410 102 140 170177 397 49 99 153 166 173 398 33 140 155 180 178 400 73 95 140 172 177400 38 115 160 171 174 386 6 124 137 180 183 400 70 124 151 191 199 3996586 96 162 184 188 400 41 112 172 181 198 399 35 149 168 182 184 399 20166 180 183 186 397 5338 102 159 202 203 393 178 101 150 195 195 3971350 104 153 185 189 400 1257 100 153 185 189 396 30 117 163 203 210 391336 105 153 188 194 399 741 101 161 193 193 396 89 100 145 172 179 39612 129 143 186 188 387 3559 91 155 177 183 392 873 102 149 194 200 3771909 100 158 202 259 400 27 122 157 171 178 395 1818 103 147 178 182 374546 102 151 179 184 397 26 132 142 195 194 400 53 117 157 176 179 397 40124 150 188 191 390 38 107 153 205 207 399 217 102 146 196 195 397 266111 147 186 184 400 76 123 157 179 186 400 9832 93 161 191 190 400 277104 162 191 189 400 65 123 165 187 189 400 31 136 163 202 202 400 5286102 166 196 201 400 102 138 166 181 182 397 30 138 158 181 181 400 64113 158 176 179 398 27 121 163 191 192 398 2943 100 165 179 181 399 25138 153 171 177 399 60 110 136 172 179 399 26 139 147 186 184 398 35 121149 176 178 397 4000 103 155 176 178 385 2390 99 157 182 184 400 28 131160 194 193 400 3545 100 161 179 180 398 15 121 146 188 187 400 2587 103158 189 192 400 86 121 165 178 184 399 3339 101 157 179 187 391 3193 101163 183 186 398 13 111 153 197 201 400 4140 102 166 191 194 400 16 130143 183 183 400 209 125 154 211 230 400 41 158 176 193 193 400 3445 94162 197 199 400 23 123 182 193 195 399 1787 100 163 204 207 400 4100 100159 Difference Difference Adjusted P between between Value of MedianMean Difference Mutant Fragments Mutant Mutant between 75th and andMutant Mode Median Mean Percentile Maximum Wild type Wild-type and cfDNAcfDNA cfDNA cfDNA cfDNA cfDNA cfDNA Wild-type Fragment Fragment FragmentFragment Fragment Fragment Fragment cfDNA Size Size Size Size Size SizeSize Fragment (bp) (bp) (bp) (bp) (bp) (bp) (bp) Size 164 159 163 170354 −3.5 −3.57 0.000 169 169 173 184 366 1.0 3.80 0.054 149 154 164 170398 −8.0 −0.35 0.816 143 182 206 284 333 16.0 36.25 0.000 154 170 108180 296 7.0 14.38 0.104 140 155 173 178 324 −9.0 −6.66 0.000 164 167 182179 329 1.5 10.09 0.479 170 156 153 168 178 −7.5 −18.98 0.411 151 164182 183 385 −6.0 1.71 0.064 168 175 193 196 399 0.0 −1.79 0.166 176 177195 195 373 3.0 11.02 0.397 175 175 181 186 312 1.0 −13.40 0.587 185 191205 219 357 21.0 23.48 0.013 175 171 183 185 394 −1.0 0.03 0.984 168 171198 240 357 −5.0 −4.34 0.571 163 171 201 258 400 0.0 5.94 0.066 168 170189 202 392 1.0 4.37 0.064 164 172 175 179 372 3.0 −10.29 0.463 141 171200 240 399 4.0 3.10 0.571 169 176 190 194 400 2.0 1.96 0.571 171 171197 229 393 −2.0 3.42 0.479 143 153 163 166 275 −14.0 −8.99 0.084 164173 195 211 398 3.0 5.92 0.001 163 164 177 181 400 −3.0 −0.39 0.880 167176 202 242 398 5.0 7.98 0.061 164 179 199 231 350 2.0 −3.82 0.685 169162 173 180 396 1.0 1.92 0.372 166 166 180 182 381 0.0 2.87 0.416 138171 183 188 351 1.5 3.29 0.572 165 169 192 198 336 −3.0 −2.86 0.451 169166 181 176 309 −1.0 4.53 0.539 180 174 185 210 326 0.5 −2.59 0.576 144163 188 212 360 −12.0 −17.11 0.004 150 166 188 204 379 −8.0 −7.53 0.208171 169 182 182 346 1.0 −3.64 0.479 166 172 180 186 399 −1.0 1.04 0.155160 176 201 200 384 3.0 9.95 0.061 166 172 198 192 371 1.0 7.08 0.560171 167 201 199 387 −4.0 14.14 0.341 168 181 201 203 400 2.0 −0.86 0.587161 179 199 209 372 −1.5 2.90 0.679 189 185 191 191 311 16.0 9.25 0.000163 167 179 176 318 0.0 −2.85 0.679 200 171 187 190 392 5.0 10.89 0.314176 176 187 192 398 0.0 −3.83 0.015 138 167 181 184 340 −1.0 2.00 0.571147 147 161 159 327 −19.0 −9.77 0.000 180 176 176 184 344 9.0 3.52 0.015360 161 197 195 360 −9.0 10.77 0.314 166 167 176 178 397 0.5 0.65 0.610164 168 178 180 400 0.0 1.78 0.314 168 167 177 179 338 −2.0 −5.83 0.463169 173 194 192 399 0.0 0.40 0.825 166 166 172 204 221 −2.0 −7.32 0.564162 169 189 186 399 −1.0 1.12 0.598 183 177 189 193 373 3.0 −0.01 0.293165 169 177 184 400 0.0 −1.73 0.598 178 173 180 186 389 1.0 0.22 0.839153 161 171 179 323 −11.0 −12.36 0.061 169 179 197 200 400 0.0 −0.320.839 143 157 173 173 325 −20.0 −18.40 0.000 175 170 196 233 357 1.012.55 0.025 197 186 215 220 374 1.0 3.72 0.603 175 174 194 194 399 0.00.65 0.714 248 224 232 260 359 47.0 34.97 0.000 163 176 192 194 400 1.0−0.85 0.718 164 173 200 202 400 −2.0 −3.65 0.062 Mutant Fragments 75th25th Mean Percentile Maximum Minimum Percentile cfDNA cfDNA cfDNA cfDNAcfDNA Fragment Fragment Fragment Fragment Fragment Size Size SizeDistinct Size Size (bp) (bp) (bp) Coverage (bp) (bp) 196 195 400 3096 79159 202 203 400 73 142 178 205 203 400 23 161 168 195 196 400 170 125158 195 192 400 2089 101 162 238 280 400 125 84 192 197 194 400 5715 108163 172 173 398 109 78 148 196 191 399 35 119 161 189 190 400 826 102162 194 195 400 95 135 160 184 184 400 27 128 150 179 184 399 4771 103161 187 185 399 7 417 154 179 179 395 330 106 152 172 177 399 536 106151 179 183 400 45 136 163 182 182 397 16 138 146 172 177 397 293 101152 171 177 399 23 130 152 180 183 399 54 104 161 184 184 400 154 96 149186 187 399 79 102 163 183 185 400 44 118 149 182 184 400 35 136 164 192191 400 13 138 164 199 205 400 50 128 155 191 193 400 81 108 150 190 191389 2597 101 159 192 197 400 58 92 173 183 189 400 74 90 147 175 178 40037 144 163 194 202 400 61 93 164 184 186 400 66 104 158 191 190 396 101126 155 188 185 394 4718 100 156 186 186 399 30 134 161 180 180 397 34139 163 182 182 400 262 101 150 182 182 400 277 101 150 180 182 395 65121 158 177 182 400 16 144 172 185 184 399 7186 100 154 181 179 394 21108 164 177 180 400 18 111 127 179 181 400 72 121 156 177 182 400 30 106160 200 199 399 36 131 147 184 185 392 20 144 173 182 184 395 16 147 156186 187 399 34 159 168 186 186 396 5 116 182 185 183 399 1073 100 142179 180 400 46 109 151 181 181 400 30 146 154 176 179 392 2742 102 154174 180 399 298 103 140 197 194 399 67 115 164 195 194 399 19 156 165178 182 395 189 105 138 183 185 398 227 123 160 185 184 397 53 78 161190 188 395 50 130 161 186 187 398 28 139 150 179 184 400 24 130 153 185185 394 48 111 154 189 187 398 2337 100 163 Difference DifferenceAdjusted P between between Value of Median Mean Difference MutantFragments Mutant Mutant between 75th and and Mutant Mode Median MeanPercentile Maximum Wild type Wild-type and cfDNA cfDNA cfDNA cfDNA cfDNAcfDNA cfDNA Wild-type Fragment Fragment Fragment Fragment FragmentFragment Fragment cfDNA Size Size Size Size Size Size Size Fragment (bp)(bp) (bp) (bp) (bp) (bp) (bp) Size 161 173 194 191 397 −1.0 −2.45 0.251178 184 237 338 377 9.0 35.30 0.114 168 171 189 186 380 −4.0 −16.380.435 173 173 188 190 400 −2.0 −6.17 0.293 169 176 203 203 400 4.5 8.800.000 194 207 243 324 400 −16.0 5.51 0.574 164 174 200 196 400 1.0 2.870.065 149 158 166 173 302 −4.0 −5.94 0.190 172 171 191 180 390 0.0 −4.340.627 166 171 187 187 395 −2.0 −1.94 0.475 161 170 182 184 400 −5.0−11.54 0.155 150 169 174 185 319 −1.0 −9.68 0.571 168 171 179 183 4000.0 0.15 0.880 154 167 164 174 117 −3.0 −22.90 0.155 165 166 178 178 361−1.0 −1.35 0.685 167 163 172 175 363 −3.0 −0.34 0.880 175 172 185 191380 3.0 6.52 0.368 146 155 162 170 224 −14.0 −19.82 0.007 169 164 170174 392 2.0 1.37 0.646 162 162 163 177 232 −4.0 −7.62 0.252 154 176 195206 383 7.5 14.58 0.064 157 163 176 185 347 −5.5 −7.87 0.154 177 174 200203 372 4.0 14.61 0.270 163 163 185 186 338 −7.0 1.98 0.039 204 181 194203 369 13.0 11.80 0.039 169 169 198 173 333 −1.0 6.05 0.610 161 171 216301 360 0.0 17.02 0.623 108 173 198 224 385 0.0 6.48 0.624 165 172 185187 397 −1.0 −5.17 0.005 192 192 202 200 397 18.0 9.79 0.007 142 167 176182 391 −6.5 −6.78 0.061 185 172 192 186 375 6.0 17.15 0.005 181 181 197211 370 8.0 3.34 0.169 194 174 189 194 379 3.5 4.60 0.270 176 176 194213 331 7.0 2.50 0.718 164 168 190 187 393 −1.0 2.54 0.113 175 175 190208 339 5.0 4.07 0.302 165 170 178 175 349 3.0 −1.65 0.407 152 165 181186 393 −4.0 −0.65 0.876 147 166 182 185 393 −3.0 0.36 0.926 161 167 186188 338 −4.0 6.15 0.234 179 179 187 180 376 10.0 9.98 0.130 167 166 183181 396 −1.0 −1.73 0.154 164 173 196 200 357 7.0 14.95 0.213 127 158 189186 352 −8.0 12.47 0.179 173 166 183 179 396 −2.0 4.31 0.427 174 174 180156 282 5.0 3.09 0.252 143 177 196 227 298 2.5 −4.24 0.479 266 178 199215 269 6.0 15.13 0.252 156 164 177 169 302 8.0 4.82 0.119 168 176 206196 365 3.0 20.55 0.415 182 185 201 192 329 12.0 14.62 0.263 164 152 157164 346 −18.0 −27.67 0.000 143 175 174 183 325 7.0 −5.22 0.054 146 168186 181 367 −0.5 5.19 0.568 164 166 176 176 387 −1.0 −0.24 0.874 148 150152 162 288 −18.0 −22.25 0.000 250 173 187 201 366 2.0 9.89 0.425 165185 197 199 361 10.0 2.20 0.154 141 150 164 175 348 −20.0 −14.58 0.000168 169 185 184 396 −2.0 1.68 0.706 175 175 189 158 392 4.0 3.80 0.241168 168 184 175 377 −4.5 −5.86 0.234 173 170 170 173 354 −2.5 −15.880.416 176 170 193 199 359 0.0 13.13 0.598 170 168 173 183 295 −3.0−11.80 0.270 166 172 187 185 394 −1.0 −1.27 0.564 Mutant Fragments 75th25th Mean Percentile Maximum Minimum Percentile cfDNA cfDNA cfDNA cfDNAcfDNA Fragment Fragment Fragment Fragment Fragment Size Size SizeDistinct Size Size (bp) (bp) (bp) Coverage (bp) (bp) 198 200 396 172 83152 190 188 400 215 123 151 184 184 400 207 121 151 191 189 397 17 143170 181 182 398 52 122 152 191 189 399 17 109 161 191 189 399 40 136 164180 181 399 127 88 149 181 186 400 68 141 166 169 179 398 10 81 167 170181 398 33 107 162 175 181 391 23 112 156 175 177 400 109 130 153 172176 400 684 105 153 179 178 398 2946 100 138 175 178 399 30 121 165 187186 400 63 140 155 181 184 400 4754 101 160 182 187 400 31 131 162 181183 400 150 110 144 179 184 400 5290 95 159 181 186 400 140 101 155 187190 397 20 92 141 190 192 400 8065 85 156 174 182 400 2586 101 147 185188 400 2808 100 150 182 187 400 2227 100 154 176 183 396 8425 100 155186 188 399 142 112 146 186 185 399 104 132 158 183 185 392 3462 101 160182 183 399 25 94 140 177 181 399 3789 101 159 181 184 400 57 131 152183 191 400 36 118 154 187 185 399 362 110 152 182 188 400 20 158 163185 187 397 23 126 151 188 189 400 2980 100 158 183 163 391 2793 91 158185 189 395 7357 100 158 184 184 398 5186 101 157 182 187 400 15595 64159 186 185 400 6749 101 158 193 190 400 23 127 148 182 185 394 3901 101160 179 180 400 4633 100 158 175 179 400 734 101 151 175 180 394 4022101 159 184 182 400 117 116 156 172 176 395 65 109 145 DifferenceDifference Adjusted P between between Value of Median Mean DifferenceMutant Fragments Mutant Mutant between 75th and and Mutant Mode MedianMean Percentile Maximum Wild type Wild-type and cfDNA cfDNA cfDNA cfDNAcfDNA cfDNA cfDNA Wild-type Fragment Fragment Fragment Fragment FragmentFragment Fragment cfDNA Size Size Size Size Size Size Size Fragment (bp)(bp) (bp) (bp) (bp) (bp) (bp) Size 160 166 193 226 396 −4.0 −4.93 0.490159 163 188 196 365 −6.0 −1.72 0.735 157 161 181 179 365 −7.0 −3.010.571 217 214 198 217 294 43.0 7.08 0.000 167 164 179 173 372 −4.5 −2.070.137 173 171 181 174 392 −1.0 −9.24 0.576 166 171 185 185 335 −1.0−5.86 0.571 131 162 168 178 311 −6.0 −11.80 0.005 175 176 198 207 3874.0 17.11 0.184 167 167 159 176 182 1.0 −10.20 0.589 167 167 174 185 3220.0 4.57 0.636 190 164 175 190 349 −4.0 −0.92 0.308 169 166 175 178 3820.0 −0.09 0.987 167 166 172 175 385 1.0 0.00 0.999 157 155 172 174 398−9.0 −7.28 0.000 165 176 198 219 325 12.0 22.37 0.007 154 167 201 215372 −3.0 13.70 0.286 170 170 179 161 393 0.0 −1.72 0.154 162 174 180 185352 2.0 2.26 0.494 166 162 176 173 385 −6.0 −5.86 0.314 167 169 179 164400 −1.0 0.11 0.909 175 167 179 180 352 −4.5 −2.77 0.589 241 168 178 209283 −3.0 −9.82 0.479 164 169 190 190 399 0.0 −0.08 0.942 165 165 169 179386 −3.5 −4.59 0.000 158 167 189 200 399 −3.0 4.17 0.007 162 171 183 190398 0.0 1.00 0.564 165 169 176 184 400 0.0 0.54 0.568 140 159 180 193352 −13.0 −5.41 0.463 159 167 189 180 331 −2.0 3.05 0.657 173 172 184167 396 1.0 0.82 0.576 140 158 159 163 341 −11.0 −23.47 0.027 168 169176 161 395 0.0 −0.66 0.576 170 170 179 184 327 −1.0 −2.41 0.568 201 182187 201 328 11.0 3.60 0.114 143 180 207 268 389 11.0 20.70 0.000 311 174198 209 311 3.0 15.25 0.475 184 168 185 185 328 −1.0 −1.49 0.571 169 170187 189 398 0.0 −0.84 0.637 167 170 161 182 389 1.0 −2.30 0.171 175 171162 187 399 −1.0 −2.37 0.008 165 170 185 186 400 1.0 1.72 0.240 167 170181 185 397 −1.0 −1.39 0.245 167 170 185 187 400 0.0 −0.52 0.702 148 194222 292 378 24.0 29.58 0.027 167 171 182 155 398 2.0 0.32 0.821 169 170185 157 400 1.0 6.16 0.000 155 165 176 178 366 −4.0 0.48 0.823 167 168172 178 399 −1.0 −2.84 0.000 156 172 199 184 399 5.0 15.08 0.084 177 167181 181 306 3.0 9.11 0.293

APPENDIX-D Table 4 Summary of whole genome cfDNA analyses High TotalQuality Analysis Patient Read Bases Bases Patient Timepoint type TypeLength Sequenced Analyzed Coverage CGCRC291 Preoperative treatment naïveWGS Colorectal Cancer 100 7232125000 4695396600 1.86 CGCRC292Preoperative treatment naïve WGS Colorectal Cancer 100 67940928004471065400 1.77 CGCRC293 Preoperative treatment naïve WGS ColorectalCancer 100 8373899600 5686176000 2.26 CGCRC294 Preoperative treatmentnaïve WGS Colorectal Cancer 100 3081312000 5347045800 2.12 CGCRC296Preoperative treatment naïve WGS Colorectal Cancer 100 100720292006770998200 2.69 CGCRC299 Preoperative treatment naïve WGS ColorectalCancer 100 10971591600 7632723200 3.03 CGCRC300 Preoperative treatmentnaïve WGS Colorectal Cancer 100 9894332600 6699951000 2.66 CGCRC301Preoperative treatment naïve WGS Colorectal Cancer 100 73573462005021002000 1.99 CGCRC302 Preoperative treatment naïve WGS ColorectalCancer 100 11671913000 8335275800 3.31 CGCRC304 Preoperative treatmentnaïve WGS Colorectal Cancer 100 19011739200 12957614200 5.14 CGCRC305Preoperative treatment naïve WGS Colorectal Cancer 100 71773414004809957200 1.91 CGCRC306 Preoperative treatment naïve WGS ColorectalCancer 100 8302233200 5608043600 2.23 CGCRC307 Preoperative treatmentnaïve WGS Colorectal Cancer 100 8034720400 5342620000 2.12 CGCRC308Preoperative treatment naïve WGS Colorectal Cancer 100 86700848005934037200 2.35 CGCRC311 Preoperative treatment naïve WGS ColorectalCancer 100 6947634400 4704601800 1.87 CGCRC315 Preoperative treatmentnaïve WGS Colorectal Cancer 100 5205544000 3419565400 1.36 CGCRC316Preoperative treatment naïve WGS Colorectal Cancer 100 64053886004447534800 1.76 CGCRC317 Preoperative treatment naïve WGS ColorectalCancer 100 6060390400 4104616600 1.63 CGCRC318 Preoperative treatmentnaïve WGS Colorectal Cancer 100 6848768600 4439404800 1.76 CGCRC319Preoperative treatment naïve WGS Colorectal Cancer 100 105452944007355181600 2.92 CGCRC320 Preoperative treatment naïve WGS ColorectalCancer 100 5961999200 3945054000 1.57 CGCRC321 Preoperative treatmentnaïve WGS Colorectal Cancer 100 8248095400 5614355000 2.23 CGCRC333Preoperative treatment naïve WGS Colorectal Cancer 100 105402676006915490600 2.74 CGCRC336 Preoperative treatment naïve WGS ColorectalCancer 100 10675581800 7087691800 2.81 CGCRC338 Preoperative treatmentnaïve WGS Colorectal Cancer 100 13788172600 8970308600 3.56 CGCRC341Preoperative treatment naïve WGS Colorectal Cancer 100 107534676007311539200 2.90 CGCRC342 Preoperative treatment naïve WGS ColorectalCancer 100 11836966000 7552793200 3.00 CGH14 Human adult elutriatedlymphocytes WGS Healthy 100 36525427600 24950300200 9.90 CGH15 Humanadult elutriated lymphocytes WGS Healthy 100 29930855000 237540494009.43 CGLU316 Pre-treatment, Day-53 WGS Lung Cancer 100 103541232006896471400 2.74 CGLU316 Pre-treatment, Day-4 WGS Lung Cancer 1007870039200 5254938800 2.09 CGLU316 Post-treatment, Day 18 WGS LungCancer 100 8155322000 5416262400 2.15 CGLU316 Post-treatment, Day 81 WGSLung Cancer 100 9442310400 6087893400 2.42 CGLU344 Pre-treatment, Day-21WGS Lung Cancer 100 8728318600 5769097200 2.29 CGLU344 Pre-treatment,Day 0 WGS Lung Cancer 100 11710246400 7826902600 3.11 CGLU344Post-treatment, Day 0.1875 WGS Lung Cancer 100 11569683000 76547016003.04 CGLU344 Post-treatment, Day 59 WGS Lung Cancer 100 110424592006320133800 2.51 CGLU369 Pre-treatment, Day-2 WGS Lung Cancer 1008630932800 5779595800 2.29 CGLU369 Post-treatment, Day 12 WGS LungCancer 100 9227709600 6136755200 2.44 CGLU369 Post-treatment, Day 68 WGSLung Cancer 100 7995282600 5239077200 2.08 CGLU369 Post-treatment, Day110 WGS Lung Cancer 100 8750541000 5626139000 2.23 CGLU373Pre-treatment, Day-2 WGS Lung Cancer 100 11746059600 7547485800 3.00CGLU373 Post-treatment, Day 0.125 WGS Lung Cancer 100 138011368009255579400 3.67 CGLU373 Post-treatment, Day 7 WGS Lung Cancer 10011537896800 7654111200 3.04 CGLU373 Post-treatment, Day 47 WGS LungCancer 100 8046326400 5397702400 2.14 CGPLBR100 Preoperative treatmentnaïve WGS Breast Cancer 100 8440532400 5729474800 2.27 CGPLBR101Preoperative treatment naïve WGS Breast Cancer 100 9786253600 66734952002.65 CGPLBR102 Preoperative treatment naïve WGS Breast Cancer 1008664980400 5669781600 2.25 CGPLBR103 Preoperative treatment naïve WGSBreast Cancer 100 9346936200 6662883400 2.64 CGPLBR104 Preoperativetreatment naïve WGS Breast Cancer 100 9443375400 6497061000 2.58CGPLBR12 Preoperative treatment naïve WGS Breast Cancer 100 70175778004823327400 1.91 CGPLBR18 Preoperative treatment naïve WGS Breast Cancer100 10309652800 7130386000 2.83 CGPLBR23 Preoperative treatment naïveWGS Breast Cancer 100 9034484800 6219625800 2.47 CGPLBR24 Preoperativetreatment naïve WGS Breast Cancer 100 9891454200 6601857400 2.62CGPLBR28 Preoperative treatment naïve WGS Breast Cancer 100 79976072005400803200 2.14 CGPLBR30 Preoperative treatment naïve WGS Breast Cancer100 5502597200 5885822400 2.34 CGPLBR31 Preoperative treatment naïve WGSBreast Cancer 100 12660085600 8551995600 3.39 CGPLBR32 Preoperativetreatment naïve WGS Breast Cancer 100 8773498600 5839034600 2.32CGPLBR33 Preoperative treatment naïve WGS Breast Cancer 100 109317428006967030600 2.76 CGPLBR34 Preoperative treatment naïve WGS Breast Cancer100 10861398600 7453225800 2.96 CGPLBR35 Preoperative treatment naïveWGS Breast Cancer 100 9180193600 6158440200 2.44 CGPLBR36 Preoperativetreatment naïve WGS Breast Cancer 100 9159948400 6091817800 2.42CGPLBR37 Preoperative treatment naïve WGS Breast Cancer 100 103075058006929530600 2.75 CGPLBR38 Preoperative treatment naïve WGS Breast Cancer100 9983824000 6841725400 2.71 CGPLBR40 Preoperative treatment naïve WGSBreast Cancer 100 10148823800 7024345400 2.79 CGPLBR41 Preoperativetreatment naïve WGS Breast Cancer 100 11168192000 7562945800 3.00CGPLBR45 Preoperative treatment naïve WGS Breast Cancer 100 87937806006011109400 2.39 CGPLBR46 Preoperative treatment naïve WGS Breast Cancer100 7228607600 4706130000 1.87 CGPLBR47 Preoperative treatment naïve WGSBreast Cancer 100 7906911400 5341655000 2.12 CGPLBR48 Preoperativetreatment naïve WGS Breast Cancer 100 6992032000 4428636200 1.76CGPLBR49 Preoperative treatment naïve WGS Breast Cancer 100 73111950004559460200 1.81 CGPLBR50 Preoperative treatment naïve WGS Breast Cancer100 11107960600 7582776600 3.01 CGPLBR51 Preoperative treatment naïveWGS Breast Cancer 100 8393547400 5102069000 2.02 CGPLBR52 Preoperativetreatment naïve WGS Breast Cancer 100 9491894800 6141729000 2.44CGPLBR55 Preoperative treatment naïve WGS Breast Cancer 100 93801098006518855200 2.59 CGPLBR56 Preoperative treatment naïve WGS Breast Cancer100 12191816800 8293011200 3.29 CGPLBR57 Preoperative treatment naïveWGS Breast Cancer 100 9847584400 6713638000 2.66 CGPLBR59 Preoperativetreatment naïve WGS Breast Cancer 100 7476477000 5059873200 2.01CGPLBR60 Preoperative treatment naïve WGS Breast Cancer 100 65313546004331253800 1.72 CGPLBR61 Preoperative treatment naïve WGS Breast Cancer100 9311029200 6430920800 2.55 CGPLBR63 Preoperative treatment naïve WGSBreast Cancer 100 8971949000 6044009600 2.40 CGPLBR65 Preoperativetreatment naïve WGS Breast Cancer 100 7197301400 4835015200 1.92CGPLBR63 Preoperative treatment naïve WGS Breast Cancer 100 100037740006974918800 2.77 CGPLBR69 Preoperative treatment naïve WGS Breast Cancer100 10080881800 6903459200 2.74 CGPLBR70 Preoperative treatment naïveWGS Breast Cancer 100 8824002800 6002533800 2.38 CGPLBR71 Preoperativetreatment naïve WGS Breast Cancer 100 10164136800 6994668600 2.78CGPLBR72 Preoperative treatment naïve WGS Breast Cancer 100 1841884140012328783000 4.89 CGPLBR73 Preoperative treatment naïve WGS Breast Cancer100 10281460200 7078613200 2.81 CGPLBR76 Preoperative treatment naïveWGS Breast Cancer 100 10105270400 6800705000 2.70 CGPLBR81 Preoperativetreatment naïve WGS Breast Cancer 100 5087126000 3273367200 1.30CGPLBR82 Preoperative treatment naïve WGS Breast Cancer 100 105764966007186662600 2.85 CGPLBR83 Preoperative treatment naïve WGS Breast Cancer100 8977124400 5947525000 2.36 CGPLBR84 Preoperative treatment naïve WGSBreast Cancer 100 6272538600 4066870600 1.61 CGPLBR87 Preoperativetreatment naïve WGS Breast Cancer 100 8460954800 5375710200 2.13CGPLBR83 Preoperative treatment naïve WGS Breast Cancer 100 86658104005499893200 2.18 CGPLBR90 Preoperative treatment naïve WGS Breast Cancer100 6663469200 4392442400 1.74 CGPLBR91 Preoperative treatment naïve WGSBreast Cancer 100 10933002400 7647842000 3.03 CGPLBR92 Preoperativetreatment naïve WGS Breast Cancer 100 10392674000 6493593000 2.58CGPLBR93 Preoperative treatment naïve WGS Breast Cancer 100 56598360003931106800 1.56 CGPLH189 Preoperative treatment naïve WGS Healthy 10011400610400 7655568800 3.04 CGPLH190 Preoperative treatment naïve WGSHealthy 100 11444671600 7581175200 3.01 CGPLH192 Preoperative treatmentnaïve WGS Healthy 100 12199010800 8126804800 3.22 CGPLH193 Preoperativetreatment naïve WGS Healthy 100 10201897600 6635285400 2.63 CGPLH194Preoperative treatment naïve WGS Healthy 100 11005087400 7081652600 2.81CGPLH196 Preoperative treatment naïve WGS Healthy 100 128914628008646881800 3.43 CGP6H197 Preoperative treatment naïve WGS Healthy 10011961841600 3052855200 3.20 CGPLH193 Preoperative treatment naïve WGSHealthy 100 13605489000 8885716000 3.53 CGPLH199 Preoperative treatmentnaïve WGS Healthy 100 1818090200 5615316000 2.23 CGPLH200 Preoperativetreatment naïve WGS Healthy 100 14400027600 9310342000 3.69 CGPLH201Preoperative treatment naïve WGS Healthy 100 6208766806 4171843400 1.66CGPLH202 Preoperative treatment naïve WGS Healthy 100 112829228007363530600 2.92 CGPLH203 Preoperative treatment naïve WGS Healthy 10013540689600 9068747600 3.60 CGPLH205 Preoperative treatment naïve WGSHealthy 100 10343537800 6696983600 2.66 CGPLH208 Preoperative treatmentnaïve WGS Healthy 100 12796300000 3272073400 3.28 CGPLH209 Preoperativetreatment naïve WGS Healthy 100 13123035400 3531813600 3.39 CGPLH210Preoperative treatment naïve WGS Healthy 100 10184218800 6832204600 2.71CGPLH211 Preoperative treatment naïve WGS Healthy 100 146552602003887067600 3.53 CGPLH300 Preoperative treatment naïve WGS Healthy 1007062083400 4553351200 1.81 CGPLH307 Preoperative treatment naïve WGSHealthy 100 7239128200 4547697200 1.80 CGPLH308 Preoperative treatmentnaïve WGS Healthy 100 8512551400 5526653600 2.19 CGPLH309 Preoperativetreatment naïve WGS Healthy 100 11664474200 7431836600 2.95 CGPLH310Preoperative treatment naïve WGS Healthy 100 11045691000 7451506200 2.96CGPLH311 Preoperative treatment naïve WGS Healthy 100 104068032006786479600 2.69 CGPLH314 Preoperative treatment naïve WGS Healthy 10010371343800 6925866600 2.75 CGPLH315 Preoperative treatment naïve WGSHealthy 100 9508538400 6208744600 2.46 CGPLH316 Preoperative treatmentnaïve WGS Healthy 100 10131063600 6891181000 2.73 CGPLH317 Preoperativetreatment naïve WGS Healthy 100 8364314400 5302232600 2.10 CGPLH319Preoperative treatment naïve WGS Healthy 100 8780528200 5585897000 2.22CGPLH320 Preoperative treatment naïve WGS Healthy 100 89562326005784619200 2.30 CGPLH322 Preoperative treatment naïve WGS Healthy 1009563837800 6445517800 2.56 CGPLH324 Preoperative treatment naïve WGSHealthy 100 6765038600 4469201600 1.77 CGPLH325 Preoperative treatmentnaïve WGS Healthy 100 8008213400 5099262800 2.02 CGPLH326 Preoperativetreatment naïve WGS Healthy 100 9554226200 6112544000 2.43 CGPLH327Preoperative treatment naïve WGS Healthy 100 8239168800 5351280200 2.12CGPLH328 Preoperative treatment naïve WGS Healthy 100 71970863004516894800 1.79 CGPLH329 Preoperative treatment naïve WGS Healthy 1008921554800 5493709800 2.18 CGPLH330 Preoperative treatment naïve WGSHealthy 100 10693603400 7077793600 2.81 CGPLH331 Preoperative treatmentnaïve WGS Healthy 100 8982792000 5538096200 2.20 CGPLH333 Preoperativetreatment naïve WGS Healthy 100 7856985400 5178829600 2.06 CGPLH335Preoperative treatment naïve WGS Healthy 100 9370663400 6035739400 2.40CGPLH336 Preoperative treatment naïve WGS Healthy 100 80024982005340331400 2.12 CGPLH337 Preoperative treatment naïve WGS Healthy 1007399022000 4954467600 1.97 CGPLH338 Preoperative treatment naïve WGSHealthy 100 8917121600 6170927200 2.45 CGPLH339 Preoperative treatmentnaïve WGS Healthy 100 8591130800 5866411400 2.33 CGPLH340 Preoperativetreatment naïve WGS Healthy 100 8046351000 5368062000 2.13 CGPLH341Preoperative treatment naïve WGS Healthy 100 7914788600 5200304800 2.06CGPLH342 Preoperative treatment naïve WGS Healthy 100 86334130005701972400 2.26 CGPLH343 Preoperative treatment naïve WGS Healthy 1006694769800 4410670860 1.75 CGPLH344 Preoperative treatment naïve WGSHealthy 100 7628192400 4961476600 1.97 CGPLH345 Preoperative treatmentnaïve WGS Healthy 100 7121569406 4747223000 1.88 CGPLH346 Preoperativetreatment naïve WGS Healthy 100 7707924600 4873321600 1.93 CGPLH35Preoperative treatment naïve WGS Healthy 100 47305985200 477418620012.63 CGPLH350 Preoperative treatment naïve WGS Healthy 100 97458398006054055200 2.40 CGPLH351 Preoperative treatment naïve WGS Healthy 10013317435800 8714465000 3.46 CGPLH352 Preoperative treatment naïve WGSHealthy 100 7059351600 4752309400 1.89 CGPLH353 Preoperative treatmentnaïve WGS Healthy 100 8435782400 5215098200 2.09 CGPLH354 Preoperativetreatment naïve WGS Healthy 100 8018644000 4857577660 1.93 CGPLH355Preoperative treatment naïve WGS Healthy 100 8624675800 5709726400 2.27CGPLH356 Preoperative treatment naïve WGS Healthy 100 88179528005729595200 2.27 CGPLH357 Preoperative treatment naïve WGS Healthy 10011931696200 7690004400 3.05 CGPLH358 Preoperative treatment naïve WGSHealthy 100 12802561200 8451274800 3.35 CGPLH36 Preoperative treatmentnaïve WGS Healthy 100 40173545600 3914810400 10.52 CGPLH360 Preoperativetreatment naïve WGS Healthy 100 7280078400 4918566200 1.95 CGPLH361Preoperative treatment naïve WGS Healthy 100 7493498400 4966813800 1.97CGPLH362 Preoperative treatment naïve WGS Healthy 100 113456442007532133600 2 99 CGPLH363 Preoperative treatment naïve WGS Healthy 1006111382800 3965952400 1.57 CGPLH364 Preoperative treatment naïve WGSHealthy 100 10823490400 7195657000 2.86 CGPLH365 Preoperative treatmentnaïve WGS Healthy 100 5938367400 3954556200 1.57 CGPLH366 Preoperativetreatment naïve WGS Healthy 100 7063168600 4731853060 1.88 CGPLH367Preoperative treatment naïve WGS Healthy 100 7119631800 4627888200 1.84CGPLH368 Preoperative treatment naïve WGS Healthy 100 77267184004975233400 1.97 CGPLH369 Preoperative treatment naïve WGS Healthy 10010967584200 7130956800 2.83 CGPLH37 Preoperative treatment naïve WGSHealthy 100 45970545400 4591328800 12.15 CGPLH370 Preoperative treatmentnaïve WGS Healthy 100 9237170006 6106373800 2.42 CGPLH371 Preoperativetreatment naïve WGS Healthy 100 8077798800 5237070600 2.08 CGPLH380Preoperative treatment naïve WGS Healthy 100 14049589200 8614241200 3.42CGPLH381 Preoperative treatment naïve WGS Healthy 100 1674379200010767862800 4.27 CGPLH382 Preoperative treatment naïve WGS Healthy 10018474025200 12276437200 4.87 CGPLH383 Preoperative treatment naïve WGSHealthy 100 13215954000 8430420600 3.36 CGPLH384 Preoperative treatmentnaïve WGS Healthy 100 8481814000 5463636260 2.17 CGPLH385 Preoperativetreatment naïve WGS Healthy 100 9596118800 6445445600 2.56 CGPLH386Preoperative treatment naïve WGS Healthy 100 7399540400 4915484800 1.95CGPLH387 Preoperative treatment naïve WGS Healthy 100 68603326004339724400 1.72 CGPLH388 Preoperative treatment naïve WGS Healthy 1008679705600 5463945400 2.17 CGPLH389 Preoperative treatment naïve WGSHealthy 100 7266863600 4702386000 1.87 CGPLH390 Preoperative treatmentnaïve WGS Healthy 100 7509035600 4913901800 1.95 CGPLH391 Preoperativetreatment naïve WGS Healthy 100 7252286000 4702404800 1.87 CGPLH392Preoperative treatment naïve WGS Healthy 100 7302618200 4722407000 1.87CGPLH393 Preoperative treatment naïve WGS Healthy 100 88791380005947871800 2.36 CGPLH394 Preoperative treatment naïve WGS Healthy 1008737031000 5599777400 2.22 CGPLH395 Preoperative treatment naïve WGSHealthy 100 7783904800 4907146000 1.95 CGPLH396 Preoperative treatmentnaïve WGS Healthy 100 7585567200 5076638200 2.01 CGPLH393 Preoperativetreatment naïve WGS Healthy 100 13001418200 8607025000 3.42 CGPLH399Preoperative treatment naïve WGS Healthy 100 9867699200 5526646000 2.19CGPLH400 Preoperative treatment naïve WGS Healthy 100 105739390006290438200 2.50 CGPLH401 Preoperative treatment naïve WGS Healthy 1009415150000 6139638000 2.44 CGPLH402 Preoperative treatment naïve WGSHealthy 100 5541458000 2912027800 1.18 CGPLH403 Preoperative treatmentnaïve WGS Healthy 100 6470913200 3549172600 1.41 CGPLH404 Preoperativetreatment naïve WGS Healthy 100 7369651800 4120205000 1.64 CGPLH405Preoperative treatment naïve WGS Healthy 100 7360239000 4293522600 1.70CGPLH406 Preoperative treatment naïve WGS Healthy 100 60261254003426007400 1.36 CGPLH407 Preoperative treatment naïve WGS Healthy 1007073375200 4079286800 1.62 CGPLH408 Preoperative treatment naïve WGSHealthy 100 8006103200 5121285600 2.03 CGPLH409 Preoperative treatmentnaïve WGS Healthy 100 7343124600 4432335600 1.76 CGPLH410 Preoperativetreatment naïve WGS Healthy 100 7551842000 4818779600 1.91 CGPLH411Preoperative treatment naïve WGS Healthy 100 6119676400 3636478400 1.44CGPLH412 Preoperative treatment naïve WGS Healthy 100 79608212004935752200 1.96 CGPLH413 Preoperative treatment naïve WGS Healthy 1007623405400 4827888400 1.92 CGPLH414 Preoperative treatment naïve WGSHealthy 100 7381312400 4743337200 1.88 CGPLH415 Preoperative treatmentnaïve WGS Healthy 100 7240754200 4162208800 1.65 CGPLH416 Preoperativetreatment naïve WGS Healthy 100 7745658600 4670226000 1.85 CGPLH417Preoperative treatment naïve WGS Healthy 100 7627498600 4403085600 1.75CGPLH418 Preoperative treatment naïve WGS Healthy 100 90902850005094814000 2.02 CGPLH419 Preoperative treatment naïve WGS Healthy 1007914120200 5078389800 2.02 CGPLH42 Preoperative treatment naïve WGSHealthy 100 39492040600 3901039400 10.32 CGPLH420 Preoperative treatmentnaïve WGS Healthy 100 70143072800 4711393600 1.87 CGPLH422 Preoperativetreatment naïve WGS Healthy 100 9103972800 6053559800 2.40 CGPLH423Preoperative treatment naïve WGS Healthy 100 10154714200 6128800200 2.43CGPLH424 Preoperative treatment naïve WGS Healthy 100 110023940006573756000 2.61 CGPLH425 Preoperative treatment naïve WGS Healthy 10014681352600 9272557000 3.68 CGPLH426 Preoperative treatment naïve WGSHealthy 100 8336731000 5177430800 2.05 CGPLH427 Preoperative treatmentnaïve WGS Healthy 100 8242924400 5632991800 2.24 CGPLH428 Preoperativetreatment naïve WGS Healthy 100 8512550400 5604756600 2.22 CGPLH429Preoperative treatment naïve WGS Healthy 100 8369802800 5477121400 2.17CGPLH43 Preoperative treatment naïve WGS Healthy 100 385131934003815698400 10.10 CGPLH430 Preoperative treatment naïve WGS Healthy 10010357365400 6841611000 2.71 CGPLH431 Preoperative treatment naïve WGSHealthy 100 7599875800 5006909000 1.99 CGPLH432 Preoperative treatmentnaïve WGS Healthy 100 7932532400 4932304200 1.96 CGPLH434 Preoperativetreatment naïve WGS Healthy 100 10417028600 6965093800 2.76 CGPLH435Preoperative treatment naïve WGS Healthy 100 6747793800 5677115290 2.29CGPLH436 Preoperative treatment naïve WGS Healthy 100 79905894005228737800 2.07 GGPLH437 Preoperative treatment naïve WGS Healthy 10010156991200 6935537200 2.75 CGPLH438 Preoperative treatment naïve WGSHealthy 100 9473604000 6445455600 2.56 CGPLH439 Preoperative treatmentnaïve WGS Healthy 100 8303723400 5439877200 2.16 CGPLH440 Preoperativetreatment naïve WGS Healthy 100 9055233800 6018631400 2.39 CGPLH441Preoperative treatment naïve WGS Healthy 100 10290682000 6896415200 2.74CGPLH442 Preoperative treatment naïve WGS Healthy 100 98765516006591249800 2.62 CGPLH443 Preoperative treatment naïve WGS Healthy 1009837225800 6360740800 2.52 CGPLH444 Preoperative treatment naïve WGSHealthy 100 9199271400 5795941660 2.26 CGPLH445 Preoperative treatmentnaïve WGS Healthy 100 8089236400 5218259800 2.07 CGPLH446 Preoperativetreatment naïve WGS Healthy 100 7890664200 5181606000 2.06 CGPLH447Preoperative treatment naïve WGS Healthy 100 7775775000 5120239800 2.03CGPLH448 Preoperative treatment naïve WGS Healthy 100 86869648005605079200 2.22 CGPLH449 Preoperative treatment naïve WGS Healthy 1008604545400 5527726600 2.19 CGPLH45 Preoperative treatment naïve WGSHealthy 100 39029653000 3771601200 9.98 CGPLH450 Preoperative treatmentnaïve WGS Healthy 100 8428254800 5439950000 2.16 CGPLH451 Preoperativetreatment naïve WGS Healthy 100 8128977600 5186265600 2.06 CGPLH452Preoperative treatment naïve WGS Healthy 100 6474313400 4216316400 1.67CGPLH453 Preoperative treatment naïve WGS Healthy 100 98318328006224917600 2.47 CGPLH455 Preoperative treatment naïve WGS Healthy 1007373753000 4593473600 1.82 CGPLH456 Preoperative treatment naïve WGSHealthy 100 8455416200 5457148200 2.17 CGPLH457 Preoperative treatmentnaïve WGS Healthy 100 8647618000 5534503800 2.20 CGPLH458 Preoperativetreatment naïve WGS Healthy 100 6633156400 4415186060 1.79 CGPLH459Preoperative treatment naïve WGS Healthy 100 8361048200 5497193800 2.18CGPLH46 Preoperative treatment naïve WGS Healthy 100 353614846003516232800 9.30 CGPLH460 Preoperative treatment naïve WGS Healthy 1006788835400 4472282800 1.77 CGPLH463 Preoperative treatment naïve WGSHealthy 100 8534880800 5481759200 2.18 CGPLH464 Preoperative treatmentnaïve WGS Healthy 100 6692520006 4184463400 1.66 CGPLH465 Preoperativetreatment naïve WGS Healthy 100 7772884600 4878430800 1.94 CGPLH466Preoperative treatment naïve WGS Healthy 100 9056275000 5830877400 2.31CGPLH467 Preoperative treatment naïve WGS Healthy 100 69314192004585861000 1.82 CGPLH468 Preoperative treatment naïve WGS Healthy 1009334067400 6314830460 2.51 CGPLH469 Preoperative treatment naïve WGSHealthy 100 7376691000 4545246600 1.80 CGPLH47 Preoperative treatmentnaïve WGS Healthy 100 38485647600 3534883600 9.35 CGPLH470 Preoperativetreatment naïve WGS Healthy 100 7899727600 5221650600 2.07 CGPLH471Preoperative treatment naïve WGS Healthy 100 9200430600 6102371000 2.42CGPLH472 Preoperative treatment naïve WGS Healthy 100 81437424005399946600 2.14 CGPLH473 Preoperative treatment naïve WGS Healthy 1008123924600 5419825400 2.15 CGPLH474 Preoperative treatment naïve WGSHealthy 100 3853071400 6084059400 2.41 CGPLH475 Preoperative treatmentnaïve WGS Healthy 100 8115374000 5291718000 2.10 CGPLH476 Preoperativetreatment naïve WGS Healthy 100 8163162000 5096869660 2.02 CGPLH477Preoperative treatment naïve WGS Healthy 100 8350093206 5465468600 2.17CGPLH478 Preoperative treatment naïve WGS Healthy 100 82596422005406516200 2.15 CGPLH479 Preoperative treatment naïve WGS Healthy 1008027598600 5417376800 2.15 CGPLH48 Preoperative treatment naïve WGSHealthy 100 42232410000 4165893400 11.02 CGPLH480 Preoperative treatmentnaïve WGS Healthy 100 7832983200 5020127000 1.99 CGPLH481 Preoperativetreatment naïve WGS Healthy 100 7578518800 4883280800 1.94 CGPLH482Preoperative treatment naïve WGS Healthy 100 8279364800 5652263600 2.24CGPLH483 Preoperative treatment naïve WGS Healthy 100 86603388005823859200 2.31 CGPLH484 Preoperative treatment naïve WGS Healthy 1008445420000 5794328000 2.30 CGPLH485 Preoperative treatment naïve WGSHealthy 100 8371255406 5490207800 2.18 CGPLH486 Preoperative treatmentnaïve WGS Healthy 100 8216712200 5506871000 2.19 CGPLH487 Preoperativetreatment naïve WGS Healthy 100 7936294200 5309250200 2.11 CGPLH488Preoperative treatment naïve WGS Healthy 100 8355603600 545316000 2.16CGPLH49 Preoperative treatment naïve WGS Healthy 100 339121918003310056000 8.76 CGPLH490 Preoperative treatment naïve WGS Healthy 1007768712400 5175567800 2.05 CGPLH491 Preoperative treatment naïve WGSHealthy 100 9070904000 6011275000 2.39 CGPLH492 Preoperative treatmentnaïve WGS Healthy 100 7208727200 4753213800 1.89 CGPLH493 Preoperativetreatment naïve WGS Healthy 100 10542882600 7225870800 2.87 CGPLH494Preoperative treatment naïve WGS Healthy 100 10908197600 7046645000 2.80CGPLH495 Preoperative treatment naïve WGS Healthy 100 89450404005891697800 2.34 CGPLH496 Preoperative treatment naïve WGS Healthy 10010859729400 7549608000 3.00 CGPLH497 Preoperative treatment naïve WGSHealthy 100 9630507400 6473162800 2.57 CGPLH498 Preoperative treatmentnaïve WGS Healthy 100 10060232600 6744622800 2.68 CGPLH499 Preoperativetreatment naïve WGS Healthy 100 10221293600 6951282800 2.76 CGPLH50Preoperative treatment naïve WGS Healthy 100 41248860600 407327289010.78 CGPLH500 Preoperative treatment naïve WGS Healthy 100 97031682096239893800 2.48 CGPLH501 Preoperative treatment naïve WGS Healthy 1009104779800 6161602800 2.45 CGPLH502 Preoperative treatment naïve WGSHealthy 100 8514467400 5290881400 2.10 CGPLH503 Preoperative treatmentnaïve WGS Healthy 100 9019992209 6100383400 2.42 CGPLH504 Preoperativetreatment naïve WGS Healthy 100 9320330200 6109750200 2.46 CGPLH505Preoperative treatment naïve WGS Healthy 100 7499497400 4914559000 1.95CGPLH506 Preoperative treatment naïve WGS Healthy 100 105261420006963312600 2.76 CGPLH507 Preoperative treatment naïve WGS Healthy 1009091018400 6146678600 2.44 CGPLH508 Preoperative treatment naïve WGSHealthy 100 10989315600 7360201400 2.92 CGPLH509 Preoperative treatmentnaïve WGS Healthy 100 9729084600 6702691600 2.66 CGPLH51 Preoperativetreatment naïve WGS Healthy 100 35967451400 3492833200 9.24 CGPLH510Preoperative treatment naïve WGS Healthy 100 11162691600 7626795400 3.03CGPLH511 Preoperative treatment naïve WGS Healthy 100 118886196008110427600 3.22 CGPLH512 Preoperative treatment naïve WGS Healthy 10010726438400 7110078000 2.82 CGPLH513 Preoperative treatment naïve WGSHealthy 100 10701564200 7105271400 2.84 CGPLH514 Preoperative treatmentnaïve WGS Healthy 100 8822067000 5958773800 2.36 CGPLH515 Preoperativetreatment naïve WGS Healthy 100 7792074800 5317464600 2.11 CGPLH516Preoperative treatment naïve WGS Healthy 100 8642620000 5846439400 2.32CGPLH517 Preoperative treatment naïve WGS Healthy 100 119159296000013937000 3.18 CGPLH518 Preoperative treatment naïve WGS Healthy 10012804517400 3606661600 3.42 CGPLH519 Preoperative treatment naïve WGSHealthy 100 11513222200 7922798400 3.14 CGPLH52 Preoperative treatmentnaïve WGS Healthy 100 49247304200 4849531400 12.83 CGPLH520 Preoperativetreatment naïve WGS Healthy 100 8942102400 6030683400 2.39 CGPLH54Preoperative treatment naïve WGS Healthy 100 45399346400 446616460011.82 CGPLH55 Preoperative treatment naïve WGS Healthy 100 425477250004283337600 11.33 CGPLH56 Preoperative treatment naïve WGS Healthy 10033460308000 3226338000 8.53 CGPLH51 Preoperative treatment naïve WGSHealthy 100 36504735200 3509125000 9.28 CGPLH59 Preoperative treatmentnaïve WGS Healthy 100 39642810600 3820011000 10.11 CGPLH625 Preoperativetreatment naïve WGS Healthy 100 6408225000 4115487600 1.63 CGPLH626Preoperative treatment naïve WGS Healthy 100 9915193600 6391657000 2.54CGPLH63 Preoperative treatment naïve WGS Healthy 100 374470476003506737000 9.26 CGPLH639 Preoperative treatment naïve WGS Healthy 1008158965890 5216049600 2.07 CGPLH64 Preoperative treatment naïve WGSHealthy 100 34275506800 3264503000 8.63 CGPLH640 Preoperative treatmentnaïve WGS Healthy 100 8058876800 5333551800 2.12 CGPLH642 Preoperativetreatment naïve WGS Healthy 100 7545555600 4909732800 1.95 CGPLH643Preoperative treatment naïve WGS Healthy 100 7865776800 5254772000 2.09CGPLH644 Preoperative treatment naïve WGS Healthy 100 68901390004599387400 1.83 CGPLH646 Preoperative treatment naïve WGS Healthy 1007757219400 5077408200 2.01 CGPLH75 Preoperative treatment naïve WGSHealthy 100 23882926000 2250344400 5.95 CGPLH76 Preoperative treatmentnaïve WGS Healthy 100 30631483600 3086042200 8.16 CGPLH77 Preoperativetreatment naïve WGS Healthy 100 31651741400 3041290200 8.04 CGPLH78Preoperative treatment naïve WGS Healthy 100 31165831200 3130079800 8.28CGPLH79 Preoperative treatment naïve WGS Healthy 100 319350430003128488200 8.27 CGPLH80 Preoperative treatment naïve WGS Healthy 10032965093000 3311371800 8.76 CGPLH81 Preoperative treatment naïve WGSHealthy 100 27035311200 2455084400 6.49 CGPLH82 Preoperative treatmentnaïve WGS Healthy 100 28447051200 2893358200 7.65 CGPLH83 Preoperativetreatment naïve WGS Healthy 100 26702240200 2459494000 6.50 CGPLH84Preoperative treatment naïve WGS Healthy 100 251713861400 25244674006.68 CGPLLU13 Pre-treatment, Day-2 WGS Lung Cancer 100 91265856005915061800 2.35 CGPLLU13 Post-treatment, Day 5 WGS Lung Cancer 1007739120200 5071745800 2.01 CGPLLU13 Post-treatment, Day 28 WGS LungCancer 100 9081585400 5764371600 2.29 CGPLLU13 Post-treatment, Day 91WGS Lung Cancer 100 9576557000 6160760200 2.44 CGPLLU14 Pre-treatment,Day-38 WGS Lung Cancer 100 13659198400 9033455800 3.58 CGPLLU14Pre-treatment, Day-16 WGS Lung Cancer 100 7178855800 4856643600 1.93CGPLLU14 Pre-treatment, Day-3 WGS Lung Cancer 100 7653473000 48161936001.91 CGPLLU14 Pre-treatment, Day 0 WGS Lung Cancer 100 73519974005193256600 2.06 CGPLLU14 Post-treatment, Day 0.33 WGS Lung Cancer 1007193040800 4869701600 1.93 CGPLLU14 Post-treatment, Day 7 WGS LungCancer 100 7102000000 4741432600 1.88 CGPLLU144 Preoperative treatmentnaïve WGS Lung Cancer 100 4934813600 3415936400 1.36 CGPLLU147Preoperative treatment naïve WGS Lung Cancer 100 24409561000 21186728005.61 CGPLLU161 Preoperative treatment naïve WGS Lung Cancer 1008998813400 6016145000 2.39 CGPLLU162 Preoperative treatment naïve WGSLung Cancer 100 9709792400 6407866400 2.54 CGPLLU163 Preoperativetreatment naïve WGS Lung Cancer 100 9150620200 6063569800 2.41 CGPLLU165Preoperative treatment naïve WGS Lung Cancer 100 28374436400 26511386007.01 CGPLLU168 Preoperative treatment naïve WGS Lung Cancer 1005692739400 3695191000 1.47 CGPLLU169 Preoperative treatment naïve WGSLung Cancer 100 9093975600 5805320800 2.30 CGPLLU175 Preoperativetreatment naïve WGS Lung Cancer 100 33794816800 3418750400 9.04CGPLLU176 Preoperative treatment naïve WGS Lung Cancer 100 87785538005794950200 2.30 CGPLLU177 Preoperative treatment naïve WGS Lung Cancer100 3734614800 2578696200 1.02 CGPLLU180 Preoperative treatment naïveWGS Lung Cancer 100 28305936600 2756034200 7.29 CGPLLU198 Preoperativetreatment naïve WGS Lung Cancer 100 32344959200 2218577200 5.86CGPLLU202 Preoperative treatment naïve WGS Lung Cancer 100 211101282001831279400 4.84 CGPLLU203 Preoperative treatment naïve WGS Lung Cancer100 4304235600 2806429000 1.15 CGPLLU205 Preoperative treatment naïveWGS Lung Cancer 100 10502467000 7386984800 2.93 CGPLLU206 Preoperativetreatment naïve WGS Lung Cancer 100 21888248200 2026666000 5.36CGPLLU207 Preoperative treatment naïve WGS Lung Cancer 100 108062306007363049000 2.92 CGPLLU208 Preoperative treatment naïve WGS Lung Cancer100 7795426800 5199545800 2.06 CGPLLU209 Preoperative treatment naïveWGS Lung Cancer 100 26174542000 2621961800 6.93 CGPLLU244 Pre-treatment,Day-7 WGS Lung Cancer 100 9967531400 6704365800 2.66 CGPLLU244Pre-treatment, Day-1 WGS Lung Cancer 100 9547119200 5785172600 2.30CGPLLU944 Post-treatment, Day 6 WGS Lung Cancer 100 95358986006452174000 2.56 CGPLLU244 Post-treatment, Day 62 WGS Lung Cancer 1006783628000 5914149000 2.35 CGPLLU245 Pre-treatment, Day-32 WGS LungCancer 100 10025823200 6313303800 2.51 CGPLLU245 Pre-treatment, Day 0WGS Lung Cancer 100 9462480400 6612867800 2.62 CGPLLU245 Post-treatment,Day 7 WGS Lung Cancer 100 9143025000 6431013200 2.55 CGPLLU245Post-treatment, Day 21 WGS Lung Cancer 100 9072713800 6368533000 2.53CGPLLU946 Pre-treatment, Day-21 WGS Lung Cancer 100 95797870006458003400 2.56 CGPLLU246 Pre-treatment, Day 0 WGS Lung Cancer 1009512703600 6440535600 2.56 CGPLLU246 Post-treatment, Day 9 WGS LungCancer 100 9012645000 6300939200 2.50 CGPLLU246 Post-treatment, Day 42WGS Lung Cancer 100 11136103000 7358747400 2.92 CGPLLU264 Pre-treatment,Day-1 WGS Lung Cancer 100 9196305000 6239803600 2.49 CGPLLU264Post-treatment, Day 6 WGS Lung Cancer 100 8247416600 5600454200 2.22CGPLLU264 Post-treatment, Day 27 WGS Lung Cancer 100 86810222005856109000 2.32 CGPLLU264 Post-treatment, Day 69 WGS Lung Cancer 1003931976400 5974246000 2.37 CGPLLU265 Pre-treatment, Day 0 WGS LungCancer 100 9460534000 6111185200 2.43 CGPLLU265 Post-treatment, Day 3WGS Lung Cancer 100 8051601200 4984166600 1.98 CGPLLU265 Post-treatment,Day 7 WGS Lung Cancer 100 8082224600 5110092600 2.03 CGPLLU265Post-treatment, Day 84 WGS Lung Cancer 100 8368637400 5369526400 2.13CGPLLU266 Pre-treatment, Day 0 WGS Lung Cancer 100 8583766400 58464736002.32 CGPLLU266 Post-treatment, Day 16 WGS Lung Cancer 100 87957936005984531400 2.37 CGPLLU266 Post-treatment, Day 83 WGS Lung Cancer 1009157947600 6227735060 2.47 CGPLLU266 Post-treatment, Day 328 WGS LungCancer 100 7299455400 5049379000 2.00 CGPLLU267 Pre-treatment, Day-1 WGSLung Cancer 100 10658657800 6892067000 2.73 CGPLLU267 Post-treatment,Day 34 WGS Lung Cancer 100 8492833400 5101097800 2.02 CGPLLU267Post-treatment, Day 90 WGS Lung Cancer 100 12030314800 7757930400 3.09CGPLLU269 Pre-treatment, Day 0 WGS Lung Cancer 100 9170168000 58304544002.31 CGPLLU269 Post-treatment, Day 9 WGS Lung Cancer 100 89056404005290461400 2.10 CGPLLU269 Post-treatment, Day 28 WGS Lung Cancer 1008455306600 5387927400 2.14 CGPLLU271 Post-treatment, Day 259 WGS LungCancer 100 8112060400 5404979000 2.14 CGPLLU271 Pre-treatment, Day 0 WGSLung Cancer 100 13150818200 8570453400 3.40 CGPLLU271 Post-treatment,Day 6 WGS Lung Cancer 100 9008880600 5854051400 2.32 CGPLLU271Post-treatment, Day 20 WGS Lung Cancer 100 8670913000 5461577000 2.17CGPLLU271 Post-treatment, Day 104 WGS Lung Cancer 100 88874414005609039000 2.23 CGPLLU43 Pre-treatment, Day-1 WGS Lung Cancer 1006407811200 5203486400 2.06 CGPLLU43 Post-treatment, Day 6 WGS LungCancer 100 9964335200 5626714400 2.23 CGPLLU43 Post-treatment, Day 27WGS Lung Cancer 100 8902283000 5485656200 2.18 CGPLLU43 Post-treatment,Day 83 WGS Lung Cancer 100 9201509200 5875064200 2.33 CGPLLU86Pre-treatment, Day 0 WGS Lung Cancer 100 9152729200 6248173200 2.48CGPLLU86 Post-treatment, Day 0.5 WGS Lung Cancer 100 67032530004663026800 1.85 CGPLLU86 Post-treatment, Day 7 WGS Lung Cancer 1006590121400 4559562400 1.81 CGPLLU86 Post-treatment, Day 17 WGS LungCancer 100 8653551800 5900136000 2.34 CGPLLU88 Pre-treatment, Day 0 WGSLung Cancer 100 8096528000 8505475400 2.18 CGPLLU88 Post-treatment, Day7 WGS Lung Cancer 100 0283192200 5784217600 2.30 CGPLLU88Post-treatment, Day 297 WGS Lung Cancer 100 9297110800 6407258000 2.54CGPLLU89 Pre-treatment, Day 0 WGS Lung Cancer 100 7042145200 53560954002.13 CGPLLU89 Post-treatment, Day 7 WGS Lung Cancer 100 72342202004930375200 1.96 CGPLLU89 Post-treatment, Day 22 WGS Lung Cancer 1006242889800 4057361000 1.61 CGPLOV11 Preoperative treatment naïve WGSOvarian Cancer 100 8985130400 5871959600 2.33 CGPLOV12 Preoperativetreatment naïve WGS Ovarian Cancer 100 9705820000 6430505400 2.55CGPLOV13 Preoperative treatment naïve WGS Ovarian Cancer 100 103079494007029712000 2.79 CCPLOV15 Preoperative treatment naïve WGS Ovarian Cancer100 8472829400 8562142400 2.21 CGPLOV16 Preoperative treatment naïve WGSOvarian Cancer 100 10977781000 7538581600 2.99 CGPLOV19 Preoperativetreatment naïve WGS Ovarian Cancer 100 8800876200 5855304000 2.32CGPLOV20 Preoperative treatment naïve WGS Ovarian Cancer 100 87144436005605165800 2.26 CGPLOV21 Preoperative treatment naïve WGS Ovarian Cancer100 10180394800 7120260400 2.83 CGPLOV22 Preoperative treatment naïveWGS Ovarian Cancer 100 10107760000 6821916800 2.71 CGPLOV23 Preoperativetreatment naïve WGS Ovarian Cancer 100 10643399800 7206330800 2.86CGPLOV24 Preoperative treatment naïve WGS Ovarian Cancer 100 67809290004623300400 1.83 CGPLOV25 Preoperative treatment naïve WGS Ovarian Cancer100 7817548600 5359975200 2.13 CGPLOV26 Preoperative treatment naïve WGSOvarian Cancer 100 11763101400 8178024400 3.25 CGPLOV28 Preoperativetreatment naïve WGS Ovarian Cancer 100 9522546400 6259423400 2.48CGPLOV31 Preoperative treatment naïve WGS Ovarian Cancer 100 91048312006109358400 2.42 CGPLOV32 Preoperative treatment naïve WGS Ovarian Cancer100 9222073600 6035150000 2.39 CGPLOV37 Preoperative treatment naïve WGSOvarian Cancer 100 8898328600 5971018200 2.37 CGPLOV38 Preoperativetreatment naïve WGS Ovarian Cancer 100 8756825200 5861536600 2.33CGPLOV40 Preoperative treatment naïve WGS Ovarian Cancer 100 97093916006654707200 2.64 CGPLOV41 Preoperative treatment naïve WGS Ovarian Cancer100 8923625000 5973070400 2.37 CGPLOV42 Preoperative treatment naïve WGSOvarian Cancer 100 10719380400 7353214200 2.92 CGPLOV43 Preoperativetreatment naïve WGS Ovarian Cancer 100 10272189000 6423288600 2.55CGPLOV44 Preoperative treatment naïve WGS Ovarian Cancer 100 98618626006769185800 2.69 CGPLOV46 Preoperative treatment naïve WGS Ovarian Cancer100 8788956400 5789863400 2.30 CGPLOV47 Preoperative treatment naïve WGSOvarian Cancer 100 9380561800 6480763600 2.57 CCPLOV48 Preoperativetreatment naïve WGS Ovarian Cancer 100 9258552600 6380106400 2.53CCPLOV49 Preoperative treatment naïve WGS Ovarian Cancer 100 87870254006134503600 2.43 CGFLOV50 Preoperative treatment naïve WGS Ovarian Cancer100 10144154400 6984721400 2.77 CGPLPA2 Preoperative treatment naïve WGSPancreatic Cancer 100 12740651400 9045622000 3.59 CGPLPA113 Preoperativetreatment naïve WGS Duodenal Canner 100 8802479000 5909030800 2.34CGPLPA114 Preoperative treatment naïve WGS Bile Duct Cancer 1008792313600 6019061000 2.39 CGPLPA115 Preoperative treatment naïve WGSBile Duct Cancer 100 8636551400 5958809000 2.36 CGPLPA117 Preoperativetreatment naïve WGS Bile Duct Cancer 100 9128885200 6288833200 2.50CGPLPA118 Preoperative treatment naïve WGS Bile Duct Cancer 1007931485800 5407532800 2.15 CGPLPA122 Preoperative treatment naïve WGSBile Duct Cancer 100 10888985000 7530118800 2.99 CGPLPA124 Preoperativetreatment naïve WGS Bile Duct Cancer 100 8062012400 5860171000 2.33CGPLPA125 Preoperative treatment naïve WGS Bile Duct Cancer 1009715576600 6390321000 2.54 CGPLPA126 Preoperative treatment naïve WGSBile Duct Cancer 100 8056768800 5651600800 2.24 CGPLPA127 Preoperativetreatment naïve WGS Bile Duct Cancer 100 8000301000 5382987600 2.14CGPLPAI28 Preoperative treatment naïve WGS Bile Duct Cancer 1006165751600 4256521400 1.69 CGPLPA129 Preoperative treatment naïve WGSBile Duct Cancer 100 7143147400 4917370400 1.95 CGPLPA130 Preoperativetreatment naïve WGS Bile Duct Cancer 100 5664335000 3603919400 1.43CGPLPA131 Preoperative treatment naïve WGS Bile Duct Cancer 1008292982000 5844942000 2.32 CGPLPA134 Preoperative treatment naïve WGSBile Duct Cancer 100 7088917000 5048887600 2.00 CGPLPA135 Preoperativetreatment naïve WGS Bile Duct Cancer 100 8750665600 5800613200 2.30CGPLPA136 Preoperative treatment naïve WGS Bile Duct Cancer 1007539715800 5248227600 2.08 CGPLPA137 Preoperative treatment naïve WGSBile Duct Cancer 100 8391815400 5901273800 2.34 CGPLPA139 Preoperativetreatment naïve WGS Bile Duct Cancer 100 8992280200 6328314400 2.51CGPLPA14 Preoperative treatment naïve WGS Pancreatic Cancer 1008787706200 5731317600 2.27 CGPLPA140 Preoperative treatment naïve WGSBile Duct Cancer 100 16365641800 11216732000 4.45 CGPLPA141 Preoperativetreatment naïve WGS Bile Duct Cancer 100 15086298000 10114790200 4.01CGPLPA15 Preoperative treatment naïve WGS Pancreatic Cancer 1008255566800 5531677600 2 20 CGPLPA155 Preoperative treatment naïve WGSBile Duct Cancer 100 9457155800 6621881800 2.63 CGPLPA156 Preoperativetreatment naïve WGS Pancreatic Cancer 100 9345385800 6728653000 2.67CGPLPA165 Preoperative treatment naïve WGS Bile Duct Cancer 1008356604600 0829895800 2.31 CGPLPA168 Preoperative treatment naïve WGSBile Duct Cancer 100 10365661600 7048115600 2.80 CGPLPA17 Preoperativetreatment naïve WGS Pancreatic Cancer 100 8073547400 4687803000 1.86CGPLPA184 Preoperative treatment naïve WGS Bile Duct Cancer 1009014218400 6230922200 2.47 CGPLPA187 Preoperative treatment naïve WGSBile Duct Cancer 100 8883536200 6140874400 2.44 CGPLPA23 Preoperativetreatment naïve WGS Pancreatic Cancer 100 9835452000 6246525400 2.48CGPLPA25 Preoperative treatment naïve WGS Pancreatic Cancer 10010077515400 6103322200 2.42 CGPLPA26 Preoperative treatment naïve WGSPancreatic Cancer 100 8354272400 5725781000 2.21 CGPLPA28 Preoperativetreatment naïve WGS Pancreatic Cancer 100 8477461600 5688846800 2.26CGPLPA33 Preoperative treatment naïve WGS Pancreatic Cancer 1007287615600 4506723800 1.82 CGPLPA34 Preoperative treatment naïve WGSPancreatic Cancer 100 6122902400 4094828000 1.62 CGPLPA37 Preoperativetreatment naïve WGS Pancreatic Cancer 100 12714888200 8527779200 3.38CGPLPA38 Preoperative treatment naïve WGS Pancreatic Cancer 1008525500600 5501341400 2.18 CGPLPA39 Preoperative treatment naïve WGSPancreatic Cancer 100 10502663600 6812333000 2.70 CGPLPA40 Preoperativetreatment naïve WGS Pancreatic Cancer 100 9083670000 0394717800 2.14CGPLPA42 Preoperative treatment naïve WGS Pancreatic Cancer 1005072126600 3800395200 1.54 CGPLPA46 Preoperative treatment naïve WGSPancreatic Cancer 100 4720090200 2626298800 1.04 CGPLPA47 Preoperativetreatment naïve WGS Pancreatic Cancer 100 7317385800 4543833000 1.80CGPLPA48 Preoperative treatment naïve WGS Pancreatic Cancer 1007553856200 5022695600 1.90 CGPLPA52 Preoperative treatment naïve WGSPancreatic Cancer 100 5655875000 3551861600 1.41 COPLPA53 Preoperativetreatment naïve WGS Pancreatic Cancer 100 9504749000 6323344800 2.51CGPLPA58 Preoperative treatment naïve WGS Pancreatic Cancer 1008088090200 5118138200 2.03 CGPLPA59 Preoperative treatment naïve WGSPancreatic Cancer 100 14547364600 9617773600 3.82 CGPLPA67 Preoperativetreatment naïve WGS Pancreatic Cancer 100 8222177400 5351172000 2.12CGPLPA69 Preoperative treatment naïve WGS Pancreatic Cancer 1007899181400 5006114800 1.90 CGPLPA71 Preoperative treatment naïve WGSPancreatic Cancer 100 7340620400 4955417400 1.97 CGPLPA74 Preoperativetreatment naïve WGS Pancreatic Cancer 100 6666371400 4571394200 1.81CGPLPA76 Preoperative treatment naïve WGS Pancreatic Cancer 1009755658600 6412606800 2.54 CGPLPA85 Preoperative treatment naïve WGSPancreatic Cancer 100 10853223000 7309498600 2.90 CGPLPA86 Preoperativetreatment naïve WGS Pancreatic Cancer 100 8744365400 5514523200 2.19CGPLPA92 Preoperative treatment naïve WGS Pancreatic Cancer 1008073791200 5390492800 2.14 CGPLPA93 Preoperative treatment naïve WGSPancreatic Cancer 100 10390273000 7186589400 2.85 CGPLPA94 Preoperativetreatment naïve WGS Pancreatic Cancer 100 11060347600 7641336400 3.03CGPLPA95 Preoperative treatment naïve WGS Pancreatic Cancer 10012416627200 7206503800 2.86 CGST102 Preoperative treatment naïve WGSPancreatic Cancer 100 6637004600 4545072600 1.80 CGST11 Preoperativetreatment naïve WGS Pancreatic Cancer 100 9718427800 6259679600 2.48CGST110 Preoperative treatment naïve WGS Pancreatic Cancer 1009319661600 6359317400 2.52 CGST114 Preoperative treatment naïve WGSPancreatic Cancer 100 6865213000 4841171600 1.92 CGST13 Preoperativetreatment naïve WGS Pancreatic Cancer 100 9284554800 6360843800 2.52CGST131 Preoperative treatment naïve WGS Gastric cancer 100 59243820003860677200 1.53 CGST141 Preoperative treatment naïve WGS Gastric cancer100 8486380800 5860491000 2.33 CGST16 Preoperative treatment naïve WGSGastric cancer 100 13820725800 9377828000 3.72 CGST18 Preoperativetreatment naïve WGS Gastric cancer 100 7781288000 5278862400 2.09 CGST21Preoperative treatment naïve WGS Gastric cancer 100 71711654004103970800 1.63 CGST26 Preoperative treatment naïve WGS Gastric cancer100 8983961800 6053405600 2.40 CGST28 Preoperative treatment naïve WGSGastric cancer 100 9683035400 6745116400 2.68 CGST30 Preoperativetreatment naïve WGS Gastric cancer 100 8684086600 5741416000 2.28 CGST32Preoperative treatment naïve WGS Gastric cancer 100 85681946005783369200 2.29 CGST33 Preoperative treatment naïve WGS Gastric cancer100 9351699600 6448718400 2.56 CGST38 Preoperative treatment naïve WGSGastric cancer 100 8409876400 5770989200 2.29 CGST39 Preoperativetreatment naïve WGS Gastric cancer 100 10573763000 7597016000 3.01CGST41 Preoperative treatment naïve WGS Gastric cancer 100 94348542006609415400 2.62 CGST45 Preoperative treatment naïve WGS Gastric cancer100 8203868600 5625223000 2.23 CGST47 Preoperative treatment naïve WGSGastric cancer 100 8938597600 6178990600 2.45 CGST48 Preoperativetreatment naïve WGS Gastric cancer 100 9106628800 6517085200 2.59 CGST53Preoperative treatment naïve WGS Gastric cancer 100 90053742005854996200 2.32 CGST58 Preoperative treatment naïve WGS Gastric cancer100 10020368600 6133458400 2.43 CGST67 Preoperative treatment naïve WGSGastric cancer 100 9198135600 5911071000 2.35 CGST77 Preoperativetreatment naïve WGS Gastric cancer 100 8228789400 5119116800 2.03 CGST80Preoperative treatment naïve WGS Gastric cancer 100 105969634007283152800 2.89 CGST81 Preoperative treatment naïve WGS Gastric cancer100 5494881200 5038064000 2.32

APPENDIX E Table 5. High coverage whole genome cfDNA analyses of healthyindividuals and lung cancer patients Correlation Correlation of GC ofCorrected Correlation Fragment Fragment of Ratio Ratio FragmentCorrelation Profile Profile Ratio of to Median to Median ProfileFragment Median Fragment Fragment to Median Ratio cfDNA Ratio RatioFragment Profile to Fragment Profile of Profile of Ratio LymphocyteAnalysis Stage at Size Healthy Healthy Profile of Nucleosome PatientPatient Type Type Timepoint Diagnosis (bp) Individuals IndividualsLymphocytes Distances CGPLH75 Healthy WGS Preoperative treatment naïveNA 168 0.977 0.952 0.920 −0.886 CGPLH77 Healthy WGS Preoperativetreatment naïve NA 166 0.970 0.960 0.904 −0.912 CGPLH80 Healthy WGSPreoperative treatment naïve NA 168 0.955 0.949 0.960 −0.917 CGPLH81Healthy WGS Preoperative treatment naïve NA 167 0.949 0.953 0.869 −0.883CGPLH82 Healthy WGS Preoperative treatment naïve NA 166 0 969 0.9490.954 −0.917 CGPLH83 Healthy WGS Preoperative treatment naïve NA 1670.949 0.939 0.919 −0.904 CGPLH84 Healthy WGS Preoperative treatmentnaïve NA 168 0 967 0.948 0.951 −0.913 CGPLH52 Healthy WGS Preoperativetreatment naïve NA 167 0.946 0.968 0.952 −0.924 CGPLH35 Healthy WGSPreoperative treatment naïve NA 166 0.981 0.973 0.945 −0.921 CGPLH37Healthy WGS Preoperative treatment naïve NA 168 0.968 0.970 0.951 −0.922CGPLH51 Healthy WGS Preoperative treatment naïve NA 167 0.968 0.9760.948 −0.925 CGPLH55 Healthy WGS Preoperative treatment naïve NA 1660.947 0.964 0.948 −0.917 CGPLH48 Healthy WGS Preoperative treatmentnaïve NA 168 0.959 0.965 0.960 −9.923 CGPLH50 Healthy WGS Preoperativetreatment naïve NA 167 0.960 0.968 0.952 −0.921 CGPLH36 Healthy WGSPreoperative treatment naïve NA 168 0.955 0.954 0.955 −0.919 CGPLH42Healthy WGS Preoperative treatment naïve NA 167 0.973 0.963 0.948 −0.918CGPLH43 Healthy WGS Preoperative treatment naïve NA 166 0.952 0.9580.953 −0.928 CGPLH59 Healthy WGS Preoperative treatment naïve NA 1680.970 0.965 0.951 −0.925 CGPLH45 Healthy WGS Preoperative treatmentnaïve NA 168 0.965 0.950 0.949 −0.911 CGPLH47 Healthy WGS Preoperativetreatment naïve NA 167 0.952 0.944 0.954 −0.921 CGPLH46 Healthy WGSPreoperative treatment naïve NA 168 0.966 0.985 0.953 −0.923 CGPLH63Healthy WGS Preoperative treatment naïve NA 168 0.977 0.968 0.939 −0.920CAPLH51 Healthy WGS Preoperative treatment naïve NA 168 0.935 0.9550.957 −0.914 CAPLH57 Healthy WGS Preoperative treatment naïve NA 1690.965 0.954 0.955 −0.917 CGPLH49 Healthy WGS Preoperative treatmentnaïve NA 168 0.958 0.951 0.950 −0.924 CGPLH56 Healthy WGS Preoperativetreatment naïve NA 166 0.940 0.957 0.959 −0.911 CGPLH64 Healthy WGSPreoperative treatment naïve NA 169 0.960 0.940 0.949 −0.918 CGPLH78Healthy WGS Preoperative treatment naïve NA 166 0.956 0.936 0.958 −0.911CGPLH79 Healthy WGS Preoperative treatment naïve NA 168 0.960 0.9570.953 −0.917 CGPLH76 Healthy WGS Preoperative treatment naïve NA 1670.969 0.965 0.953 −0.917 CGPLLU175 Lung Cancer WGS Preoperativetreatment naïve I 165 0.316 0.284 0.244 −0.262 CGPLLU180 Lung Cancer WGSPreoperative treatment naïve I 166 0.907 0.846 0.826 −0.819 CGPLLU198Lung Cancer WGS Preoperative treatment naïve I 166 0.972 0.946 0.928−0.911 CGPLLU202 Lung Cancer WGS Preoperative treatment naïve I 1600.821 0.605 0.905 −0.843 CGPLLU165 Lung Cancer WGS Preoperativetreatment naïve II 163 0.924 0.961 0.815 −0.851 CGPLLU209 Lung CancerWGS Preoperative treatment naïve II 163 0.578 0.526 0.513 −0.534CGPLLU147 Lung Cancer WGS Preoperative treatment naïve III 166 0.9530.919 0.939 −0.912 CGPLLU206 Lung Cancer WGS Preoperative treatmentnaïve III 158 0.488 0.343 0.460 −0.481

APPENDIX F Table 6. Monitoring response to therapy using whole genomeanalyses of cfDNA fragmentation profiles and targeted mutations analysesProgression- free Survival Patient Patient Type Analysis Type TimepointStage (months) CGPLLU14 Lung Cancer Targeted Mutation Analysis and WGSPre-treatment, Day-38 IV 15.4 CGPLLU14 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day-16 IV 15.4 CGPLLU14 Lung CancerTargeted Mutation Analysis and WGS Pre-treatment, Day-3 IV 15.4 CGPLLU14Lung Cancer Targeted Mutation Analysis and WGS Pre-treatment, Day 0 IV15.4 CGPLLU14 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 0.33 IV 15.4 CGPLLU14 Lung Cancer Targeted MutationAnalysis and WGS Post-treatment, Day 7 IV 15.4 CGPLLU88 Lung CancerTargeted Mutation Analysis and WGS Pre-treatment, Day 0 IV 18.0 CGPLLU88Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 7 IV18.0 CGPLLU88 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 297 IV 18.0 CGPLLU244 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day-7 IV 1.2 CGPLLU244 Lung CancerTargeted Mutation Analysis and WGS Pre-treatment, Day-1 IV 1.2 CGPLLU244Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 6 IV1.2 CGPLLU244 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 62 IV 1.2 CGPLLU245 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day-32 IV 1.7 CGPLLU245 Lung CancerTargeted Mutation Analysis and WGS Pre-treatment, Day 0 IV 1.7 CGPLLU245Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 7 IV1.7 CGPLLU245 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 21 IV 1.7 CGPLLU246 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day-21 IV 1.3 CGPLLU246 Lung CancerTargeted Mutation Analysis and WGS Pre-treatment, Day 0 IV 1.3 CGPLLU246Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 9 IV1.3 CGPLLU246 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 42 IV 1.1 CGPLLU86 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day 0 IV 12.4 CGPLLU86 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 0.5 IV 12.4CGPLLU86 Lung Cancer Targeted Mutation Analysis and WGS Post-treatment,Day 7 IV 12.4 CGPLLU86 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 17 IV 12.4 CGPLLU89 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day 0 IV 6.7 CGPLLU89 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 7 IV 6.7 CGPLLU89Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 22 IV6.7 CGLU316 Lung Cancer Targeted Mutation Analysis and WGSPre-treatment, Day-53 IV 1.4 CGLU316 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day-4 IV 1.4 CGLU316 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 18 IV 1.4 CGLU316Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 87 IV1.4 CGLU344 Lung Cancer Targeted Mutation Analysis and WGSPre-treatment, Day-21 IV Ongoing CGLU344 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day 0 IV Ongoing CGLU344 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 0.1675 IV OngoingCGLU344 Lung Cancer Targeted Mutation Analysis and WGS Post-treatment,Day 59 IV Ongoing CGLU369 Lung Cancer Targeted Mutation Analysis and WGSPre-treatment, Day-2 IV 7.5 CGLU369 Lung Cancer Targeted MutationAnalysis and WGS Post-treatment, Day 12 IV 7.5 CGLU369 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 68 IV 7.5 CGLU369Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 110IV 7.5 CGLU373 Lung Cancer Targeted Mutation Analysis and WGSPre-treatment, Day-2 IV Ongoing CGLU373 Lung Cancer Targeted MutationAnalysis and WGS Post-treatment, Day 0.125 IV Ongoing CGLU373 LungCancer Targeted Mutation Analysis and WGS Post-treatment, Day 7 IVOngoing CGLU373 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 47 IV Ongoing CGPLLU13 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day-2 IV 1.5 CGPLLU13 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 5 IV 1.5 CGPLLU13Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 28 IV1.5 CGPLLU13 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 91 IV 1.5 CGPLLU264 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day-1 IV Ongoing CGPLLU264 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 6 IV OngoingCGPLLU264 Lung Cancer Targeted Mutation Analysis and WGS Post-treatment,Day 27 IV Ongoing CGPLLU264 Lung Cancer Targeted Mutation Analysis andWGS Post-treatment, Day 69 IV Ongoing CGPLLU265 Lung Cancer TargetedMutation Analysis and WGS Pre-treatment, Day 0 IV Ongoing CGPLLU265 LungCancer Targeted Mutation Analysis and WGS Post-treatment, Day 3 IVOngoing CGPLLU265 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 7 IV Ongoing CGPLLU265 Lung Cancer Targeted MutationAnalysis and WGS Post-treatment, Day 84 IV Ongoing CGPLLU266 Lung CancerTargeted Mutation Analysis and WGS Pre-treatment, Day 0 IV 9.6 CGPLLU266Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 16 IV9.6 CGPLLU266 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 83 IV 9.6 CGPLLU266 Lung Cancer Targeted MutationAnalysis and WGS Post-treatment, Day 328 IV 9.6 CGPLLU267 Lung CancerTargeted Mutation Analysis and WGS Pre-treatment, Day-1 IV 3.9 CGPLLU267Lung Cancer Targeted Mutation Analysis and WGS Post-treatment, Day 34 IV3.9 CGPLLU267 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 90 IV 3.9 CGPLLU269 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day 0 IV Ongoing CGPLLU269 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 9 IV OngoingCGPLLU269 Lung Cancer Targeted Mutation Analysis and WGS Post-treatment,Day 28 IV Ongoing CGPLLU271 Lung Cancer Targeted Mutation Analysis andWGS Pre-treatment, Day 0 IV 8.2 CGPLLU271 Lung Cancer Targeted MutationAnalysis and WGS Post-treatment, Day 6 IV 8.2 CGPLLU271 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 20 IV 8.2CGPLLU271 Lung Cancer Targeted Mutation Analysis and WGS Post-treatment,Day 104 IV 8.2 CGPLLU271 Lung Cancer Targeted Mutation Analysis and WGSPost-treatment, Day 259 IV 8.2 CGPLLU43 Lung Cancer Targeted MutationAnalysis and WGS Pre-treatment, Day-1 IV Ongoing CGPLLU43 Lung CancerTargeted Mutation Analysis and WGS Post-treatment, Day 6 IV OngoingCGPLLU43 Lung Cancer Targeted Mutation Analysis and WGS Post-treatment,Day 27 IV Ongoing CGPLLU43 Lung Cancer Targeted Mutation Analysis andWGS Post-treatment, Day 83 IV Ongoing Correlation of Fragment RatioCorrelation Profile to of Median Fragment Fragment Ratio Ratio Profileto Maximum Profile of Lymphocyte Mutant Healthy Nucleosome AllelePatient Individuals Distances Targeted Mutation Fraction CGPLLU14 0.941−0.841 EGFR 861L > Q 0.89% CGPLLU14 0.933 −0.833 EGFR 861L > Q 0.18%CGPLLU14 0.908 −0.814 EGFR 719G > S 0.49% CGPLLU14 0.883 −0.752 EGFR861L > Q 1.39% CGPLLU14 0.820 −0.692 EGFR 719G > S 1.05% CGPLLU14 0.927−0.887 EGFR 861L > Q 0.00% CGPLLU88 0.657 −0.584 EGFR 7459ELREA > T9.06% CGPLLU88 0.939 −0.799 EGFR 790T > M 0.15% CGPLLU88 0.946 −0.869EGFR 7459ELREA > T 0.93% CGPLLU244 0.850 −0.706 EGFR 858L > R 4.98%CGPLLU244 0.867 −0.764 EGFR 62L > R 3.41% CGPLLU244 0.703 −0.639 EGFR858L > R 5.57% CGPLLU244 0.659 −0.660 EGFR 858L > R 11.80% CGPLLU2450.871 −0.724 EGFR 745KELREA > K 10.60% CGPLLU245 0.736 −0.608 EGFR745KELREA > K 14.10% CGPLLU245 0.731 −0.559 EGFR 745KELREA > K 8.56%CGPLLU245 0.613 −0.426 EGFR 745KELREA > K 10.69% CGPLLU246 0.897 −0.757EGFR 790T > M 0.49% CGPLLU246 0.469 −0.376 EGFR 858L > R 6.17% CGPLLU2460.874 −0.746 EGFR 858L > R 1.72% CGPLLU246 0.775 −0.665 EGFR 858L > R5.29% CGPLLU86 0.817 −0.630 EGFR 746ELREATS > D 0.00% CGPLLU86 0.916−0.811 EGFR 746ELREATS > D 0.19% CGPLLU86 0.859 −0.694 EGFR 746ELREATS >D 0.00% CGPLLU86 0.932 −0.848 EGFR 746ELREATS > D 0.00% CGPLLU89 0.864−0.729 EGFR 747LREATS > − 0.42% CGPLLU89 0.908 −0.803 EGFR 747LREATS > −0.20% CGPLLU89 0.853 −0.881 EGFR 747LREATS > − 0.00% CGLU316 0.331−0.351 EGFR L861Q 15.72% CGLU316 0.225 −0.253 EGFR L861Q 45.67% CGLU3160.336 −0.364 EGFR G719A 33.38% CGLU316 0.340 −0.364 EGFR L861Q 66.01%CGLU344 0.935 −0.818 EGFR E746_A75Cdel 0.00% CGLU344 0.919 −0.774 EGFRE746_A75Cdel 0.22% CGLU344 0.953 −0.860 EGFR E746_A75Cdel 0.40% CGLU3440.944 −0.832 EGFR E746_A75Cdel 0.00% CGLU369 0.825 −0.826 EGFR L858R20.61% CGLU369 0.950 −0.903 EGFR L858R 0.22% CGLU369 0.945 −0.889 EGFRL858R 0.16% CGLU369 0.886 −0.883 EGFR L858R 0.10% CGLU373 0.922 −0.804EGFR E746_A75Cdel 0.82% CGLU373 0.959 −0.853 EGFR E746_A75Cdel 0.00%CGLU373 0.967 −0.886 EGFR E746_A75Cdel 0.15% CGLU373 0.951 −0.890 EGFRE746_A75Cdel 0.00% CGPLLU13 0.425 −0.400 EGFR E746_A75Cdel 7.66%CGPLLU13 0.272 −0.257 EGFR E746_A75Cdel 13.10% CGPLLU13 0.584 −0.536EGFR E746_A75Cdel 6.09% CGPLLU13 0.530 −0.513 EGFR E746_A75Cdel 9.28%CGPLLU264 0.946 −0.824 EGFR D761N 0.00% CGPLLU264 0.927 −0.788 EGFRD761N 0.16% CGPLLU264 0.962 −0.856 EGFR D761N 0.00% CGPLLU264 0.960−0.894 EGFR D761N 0.00% CGPLLU265 0.953 −0.859 EGFR L858R 0.21%CGPLLU265 0.949 −0.842 EGFR L858R 0.21% CGPLLU265 0.955 −0.844 EGFRT790M 0.21% CGPLLU265 0.946 −0.825 EGFR L858R 0.00% CGPLLU266 0.951−0.904 NA 0.00% CGPLLU266 0.959 −0.886 NA 0.00% CGPLLU266 0.961 −0.880NA 0.00% CGPLLU266 0.958 −0.855 NA 0.00% CGPLLU267 0.919 −0.863 EGFRL858R 1.93% CGPLLU267 0.863 −0.889 EGFR L858R 0.14% CGPLLU267 0.962−0.876 EGFR L858R 0.38% CGPLLU269 0.951 −0.864 EGFR L858R 0.10%CGPLLU269 0.941 −0.694 EGFR L858R 0.00% CGPLLU269 0.957 −0.676 EGFRL858R 0.00% CGPLLU271 0.871 −0.284 EGFR E746_A75Cdel 3.36% CGPLLU2710.947 −0.826 EGFR E746_A75Cdel 0.17% CGPLLU271 0.952 −0.839 EGFRE746_A75Cdel 0.00% CGPLLU271 0.944 −0.810 EGFR E746_A75Cdel 0.00%CGPLLU271 0.950 −0.831 EGFR E746_A75Cdel 0.44% CGPLLU43 0.944 −0.903 NA0.00% CGPLLU43 0.956 −0.899 NA 0.00% CGPLLU43 0.959 −0.901 NA 0.00%CGPLLU43 0.965 −0.896 NA 0.00%

APPENDIX-G Table 7 Whole genome cfDNA analyses in healthy individualsand cancer patients Correlation of Fragment Ratio Profile to MedianMedian Fragment cfDNA Ratio Size Profile Stage at Fragment of HealthyPatient Patient Type Analysis Type Timepoint Diagnosis (bp) IndividualsCGCRC291 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve V 163 0.1972 CGCRC292 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve V 1660.7604 CGCRC293 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve V 166 0.9335 CGCRC294 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1660.6531 CGCRC296 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 166 0.8161 CGCRC299 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1620.7325 CGCRC300 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 167 0.9382 CGCRC301 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1650.8252 CGCRC302 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 163 0.7499 CGCRC304 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1620.4642 CGCRC305 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 165 0.8909 CGCRC306 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1650.8523 CGCRC307 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 165 0.9140 CGCRC308 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1650.8734 CGCRC311 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 166 0.8535 CGCRC315 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1670.6083 CGCRC316 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve III 161 0.1546 CGCRC317 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1630.6242 CGCRC318 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 166 0.8824 CGCRC319 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1600.5979 CGCRC320 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 167 0.7949 CGCRC321 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1640.7804 CGCRC333 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve V 163 0.4263 CGCRC335 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve V 1620.6466 CGCRC338 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve V 162 0.7740 CGCRC341 Colorectal CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve V 1640.8995 CGCRC342 Colorectal Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve V 158 0.2524 CGPLBR100 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1660.9440 CGPLBR101 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 169 0.8864 CGPLBR102 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1680.9617 CGPLBR103 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 167 0.9498 CGPLBR104 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1640.8490 CGPLBR12 Breast Cancer WGS Preoperative treatment naïve III 1630.8350 CGPLBR18 Breast Cancer WGS Preoperative treatment naïve II 1660.8411 CGPLBR23 Breast Cancer WGS Preoperative treatment naïve II 1560.9714 CGPLBR24 Breast Cancer WGS Preoperative treatment naïve III 1660.8402 CGPLBR28 Breast Cancer WGS Preoperative treatment naïve II 1610.9584 CGPLBR30 Breast Cancer WGS Preoperative treatment naïve II 1670.6951 CGPLBR31 Breast Cancer WGS Preoperative treatment naïve II 1660.9719 CGPLBR32 Breast Cancer WGS Preoperative treatment naïve II 1660.9590 CGPLBR33 Breast Cancer WGS Preoperative treatment naïve II 1630.9706 CGPLBR34 Breast Cancer WGS Preoperative treatment naïve II 1680.8735 CGPLBR35 Breast Cancer WGS Preoperative treatment naïve II 1690.9655 CGPLBR36 Breast Cancer WGS Preoperative treatment naïve II 1670.9394 CGPLBR37 Breast Cancer WGS Preoperative treatment naïve I 1650.9691 CGPLBR38 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve III 167 0.9105 CGPLBR40 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1680.9273 CGPLBR41 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 164 0.9626 CGPLBR45 Breast Cancer WGSPreoperative treatment naïve III 168 0.9615 CGPLBR46 Breast Cancer WGSPreoperative treatment naïve I 166 0.9322 CGPLBR47 Breast Cancer WGSPreoperative treatment naïve II 169 0.9461 CGPLBR48 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1710.7686 CGPLBR49 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 160 0.8867 CGPLBR50 Breast Cancer WGSPreoperative treatment naïve II 165 0.8593 CGPLBR51 Breast Cancer WGSPreoperative treatment naïve III 164 0.9359 CGPLBR52 Breast Cancer WGSPreoperative treatment naïve III 165 0.8688 CGPLBR55 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1630.9634 CGPLBR56 Breast Cancer WGS Preoperative treatment naïve III 1660.9459 CGPLBR57 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 168 0.9672 CGPLBR59 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1670.9438 CGPLBR60 Breast Cancer WGS Preoperative treatment naïve II 1630.9479 CGPLBR61 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 165 0.9611 CGPLBR63 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1680.9555 CGPLBR65 Breast Cancer WGS Preoperative treatment naïve II 1670.9506 CGPLBR68 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve III 163 0.9154 CGPLBR69 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1650.9460 CGPLBR70 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 168 0.9651 CGPLBR71 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1650.9577 CGPLBR72 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 167 0.9786 CGPLBR73 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1670.9576 CGPLBR76 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 170 0.9410 CGPLBR81 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1700.9643 CGPLBR82 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 166 0.9254 CGPLBR83 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1690.9451 CGPLBR84 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve III 169 0.9315 CGPLBR87 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1660.9154 CGPLBR88 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 169 0.9370 CGPLBR90 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1690.9002 CGPLBR91 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve III 164 0.7955 CGPLBR92 Breast CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1620.6774 CGPLBR93 Breast Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 164 0.8773 CGPLH189 Healthy WGSPreoperative treatment naïve NA 168 0.9325 CGPLH190 Healthy WGSPreoperative treatment naïve NA 167 0.9403 CGPLH192 Healthy WGSPreoperative treatment naïve NA 167 0.9646 CGPLH193 Healthy WGSPreoperative treatment naïve NA 167 0.9423 CGPLH194 Healthy WGSPreoperative treatment naïve NA 168 0.9567 CGPLH196 Healthy WGSPreoperative treatment naïve NA 167 0.9709 CGPLH197 Healthy WGSPreoperative treatment naïve NA 166 0.9605 CGPLH198 Healthy WGSPreoperative treatment naïve NA 167 0.9238 CGPLH199 Healthy WGSPreoperative treatment naïve NA 165 0.9618 CGPLH200 Healthy WGSPreoperative treatment naïve NA 167 0.9183 CGPLH201 Healthy WGSPreoperative treatment naïve NA 168 0.9548 CGPLH202 Healthy WGSPreoperative treatment naïve NA 168 0.9471 CGPLH203 Healthy WGSPreoperative treatment naïve NA 167 0.9534 CGPLH205 Healthy WGSPreoperative treatment naïve NA 168 0.9075 CGPLH208 Healthy WGSPreoperative treatment naïve NA 168 0.9422 CGPLH209 Healthy WGSPreoperative treatment naïve NA 169 0.9556 CGPLH210 Healthy WGSPreoperative treatment naïve NA 169 0.9447 CGPLH211 Healthy WGSPreoperative treatment naïve NA 169 0.9538 CGPLH300 Healthy WGSPreoperative treatment naïve NA 168 0.9019 CGPLH307 Healthy WGSPreoperative treatment naïve NA 168 0.9576 CGPLH308 Healthy WGSPreoperative treatment naïve NA 168 0.9481 CGPLH309 Healthy WGSPreoperative treatment naïve NA 168 0.9672 CGPLH310 Healthy WGSPreoperative treatment naïve NA 165 0.9547 CGPLH311 Healthy WGSPreoperative treatment naïve NA 167 0.9302 CGPLH314 Healthy WGSPreoperative treatment naïve NA 167 0.9482 CGPLH315 Healthy WGSPreoperative treatment naïve NA 167 0.8659 CGPLH316 Healthy WGSPreoperative treatment naïve NA 165 0.9374 CGPLH317 Healthy WGSPreoperative treatment naïve NA 169 0.9542 CGPLH319 Healthy WGSPreoperative treatment naïve NA 167 0.9578 CGPLH320 Healthy WGSPreoperative treatment naïve NA 164 0.8913 CGPLH322 Healthy WGSPreoperative treatment naïve NA 167 0.8751 CGPLH324 Healthy WGSPreoperative treatment naïve NA 169 0.9519 CGPLH325 Healthy WGSPreoperative treatment naïve NA 167 0.9124 CGPLH326 Healthy WGSPreoperative treatment naïve NA 166 0.9574 CGPLH327 Healthy WGSPreoperative treatment naïve NA 168 0.9533 CGPLH328 Healthy WGSPreoperative treatment naïve NA 166 0.9643 CGPLH329 Healthy WGSPreoperative treatment naïve NA 167 0.9609 CGPLH330 Healthy WGSPreoperative treatment naïve NA 167 0.9118 CGPLH331 Healthy WGSPreoperative treatment naïve NA 166 0.9679 CGPLH333 Healthy WGSPreoperative treatment naïve NA 169 0.9474 CGPLH335 Healthy WGSPreoperative treatment naïve NA 167 0.8909 CGPLH336 Healthy WGSPreoperative treatment naïve NA 169 0.9248 CGPLH337 Healthy WGSPreoperative treatment naïve NA 167 0.9533 CGPLH338 Healthy WGSPreoperative treatment naïve NA 165 0.9388 CGPLH339 Healthy WGSPreoperative treatment naïve NA 167 0.9396 CGPLH340 Healthy WGSPreoperative treatment naïve NA 167 0.9488 CGPLH341 Healthy WGSPreoperative treatment naïve NA 166 0.9533 CGPLH342 Healthy WGSPreoperative treatment naïve NA 166 0.7858 CGPLH343 Healthy WGSPreoperative treatment naïve NA 167 0.9421 CGPLH344 Healthy WGSPreoperative treatment naïve NA 169 0.9192 CGPLH345 Healthy WGSPreoperative treatment naïve NA 169 0.9345 CGPLH346 Healthy WGSPreoperative treatment naïve NA 169 0.9475 CGPLH350 Healthy WGSPreoperative treatment naïve NA 171 0.9570 CGPLH351 Healthy WGSPreoperative treatment naïve NA 168 0.8176 CGPLH352 Healthy WGSPreoperative treatment naïve NA 168 0.9521 CGPLH353 Healthy WGSPreoperative treatment naïve NA 167 0.9435 CGPLH354 Healthy WGSPreoperative treatment naïve NA 168 0.9481 CGPLH355 Healthy WGSPreoperative treatment naïve NA 167 0.9613 CGPLH356 Healthy WGSPreoperative treatment naïve NA 168 0.9474 CGPLH357 Healthy WGSPreoperative treatment naïve NA 167 0.9255 CGPLH358 Healthy WGSPreoperative treatment naïve NA 167 0.7777 CGPLH360 Healthy WGSPreoperative treatment naïve NA 168 0.8500 CGPLH361 Healthy WGSPreoperative treatment naïve NA 167 0.9261 CGPLH362 Healthy WGSPreoperative treatment naïve NA 167 0.9236 CGPLH363 Healthy WGSPreoperative treatment naïve NA 167 0.9488 CGPLH364 Healthy WGSPreoperative treatment naïve NA 168 0.9311 CGPLH365 Healthy WGSPreoperative treatment naïve NA 165 0.9371 CGPLH366 Healthy WGSPreoperative treatment naïve NA 167 0.9536 CGPLH367 Healthy WGSPreoperative treatment naïve NA 166 0.8748 CGPLH368 Healthy WGSPreoperative treatment naïve NA 169 0.9490 CGPLH369 Healthy WGSPreoperative treatment naïve NA 167 0.9428 CGPLH370 Healthy WGSPreoperative treatment naïve NA 167 0.9642 CGPLH371 Healthy WGSPreoperative treatment naïve NA 168 0.9621 CGPLH380 Healthy WGSPreoperative treatment naïve NA 170 0.9652 CGPLH381 Healthy WGSPreoperative treatment naïve NA 169 0.9541 CGPLH382 Healthy WGSPreoperative treatment naïve NA 167 0.9380 CGPLH383 Healthy WGSPreoperative treatment naïve NA 168 0.9700 CGPLH384 Healthy WGSPreoperative treatment naïve NA 169 0.8061 CGPLH385 Healthy WGSPreoperative treatment naïve NA 167 0.8856 CGPLH386 Healthy WGSPreoperative treatment naïve NA 167 0.6920 CGPLH387 Healthy WGSPreoperative treatment naïve NA 169 0.9583 CGPLH388 Healthy WGSPreoperative treatment naïve NA 167 0.9348 CGPLH389 Healthy WGSPreoperative treatment naïve NA 168 0.9409 CGPLH390 Healthy WGSPreoperative treatment naïve NA 167 0.9216 CGPLH391 Healthy WGSPreoperative treatment naïve NA 166 0.9334 CGPLH392 Healthy WGSPreoperative treatment naïve NA 167 0.9165 CGPLH393 Healthy WGSPreoperative treatment naïve NA 169 0.9256 CGPLH394 Healthy WGSPreoperative treatment naïve NA 167 0.9257 CGPLH395 Healthy WGSPreoperative treatment naïve NA 166 0.8611 CGPLH396 Healthy WGSPreoperative treatment naïve NA 167 0.7884 CGPLH398 Healthy WGSPreoperative treatment naïve NA 167 0.9463 CGPLH399 Healthy WGSPreoperative treatment naïve NA 169 0.8780 CGPLH400 Healthy WGSPreoperative treatment naïve NA 168 0.6662 CGPLH401 Healthy WGSPreoperative treatment naïve NA 167 0.9428 CGPLH402 Healthy WGSPreoperative treatment naïve NA 167 0.9353 CGPLH403 Healthy WGSPreoperative treatment naïve NA 168 0.9329 CGPLH404 Healthy WGSPreoperative treatment naïve NA 169 0.9402 CGPLH405 Healthy WGSPreoperative treatment naïve NA 166 0.9579 CGPLH406 Healthy WGSPreoperative treatment naïve NA 167 0.8188 CGPLH407 Healthy WGSPreoperative treatment naïve NA 169 0.9527 CGPLH408 Healthy WGSPreoperative treatment naïve NA 167 0.9584 CGPLH049 Healthy WGSPreoperative treatment naïve NA 168 0.9220 CGPLH410 Healthy WGSPreoperative treatment naïve NA 168 0.9102 CGPLH411 Healthy WGSPreoperative treatment naïve NA 167 0.9392 CGPLH412 Healthy WGSPreoperative treatment naïve NA 167 0.9561 CGPLH413 Healthy WGSPreoperative treatment naïve NA 167 0.9451 CGPLH414 Healthy WGSPreoperative treatment naïve NA 168 0.9258 CGPLH415 Healthy WGSPreoperative treatment naïve NA 169 0.9217 CGPLH416 Healthy WGSPreoperative treatment naïve NA 167 0.9672 CGPLH417 Healthy WGSPreoperative treatment naïve NA 168 0.9578 CGPLH418 Healthy WGSPreoperative treatment naïve NA 169 0.9376 CGPLH419 Healthy WGSPreoperative treatment naïve NA 167 0.9228 CGPLH420 Healthy WGSPreoperative treatment naïve NA 169 0.9164 CGPLH422 Healthy WGSPreoperative treatment naïve NA 166 0.9069 CGPLH423 Healthy WGSPreoperative treatment naïve NA 169 0.9606 CGPLH424 Healthy WGSPreoperative treatment naïve NA 167 0.9553 CGPLH425 Healthy WGSPreoperative treatment naïve NA 168 0.9722 CGPLH426 Healthy WGSPreoperative treatment naïve NA 168 0.9560 CGPLH427 Healthy WGSPreoperative treatment naïve NA 167 0.9594 CGPLH428 Healthy WGSPreoperative treatment naïve NA 167 0.9591 CGPLH429 Healthy WGSPreoperative treatment naïve NA 168 0.9358 CGPLH430 Healthy WGSPreoperative treatment naïve NA 167 0.9639 CGPLH431 Healthy WGSPreoperative treatment naïve NA 167 0.9570 CGPLH432 Healthy WGSPreoperative treatment naïve NA 168 0.9485 CGPLH434 Healthy WGSPreoperative treatment naïve NA 168 0.9671 CGPLH435 Healthy WGSPreoperative treatment naïve NA 170 0.9133 CGPLH436 Healthy WGSPreoperative treatment naïve NA 168 0.9360 CGPLH437 Healthy WGSPreoperative treatment naïve NA 170 0.9445 CGPLH438 Healthy WGSPreoperative treatment naïve NA 170 0.9537 CGPLH439 Healthy WGSPreoperative treatment naïve NA 171 0.9547 CGPLH440 Healthy WGSPreoperative treatment naïve NA 169 0.9562 CGPLH441 Healthy WGSPreoperative treatment naïve NA 167 0.9660 CGPLH442 Healthy WGSPreoperative treatment naïve NA 167 0.9569 CGPLH443 Healthy WGSPreoperative treatment naïve NA 170 0.9431 CGPLH444 Healthy WGSPreoperative treatment naïve NA 171 0.9429 CGPLH445 Healthy WGSPreoperative treatment naïve NA 171 0.9446 CGPLH446 Healthy WGSPreoperative treatment naïve NA 167 0.9502 CGPLH447 Healthy WGSPreoperative treatment naïve NA 169 0.9421 CGPLH448 Healthy WGSPreoperative treatment naïve NA 167 0.9553 CGPLH449 Healthy WGSPreoperative treatment naïve NA 167 0.9550 CGPLH450 Healthy WGSPreoperative treatment naïve NA 167 0.9572 CGPLH451 Healthy WGSPreoperative treatment naïve NA 169 0.9548 CGPLH452 Healthy WGSPreoperative treatment naïve NA 167 0.9498 CGPLH453 Healthy WGSPreoperative treatment naïve NA 166 0.9572 CGPLH455 Healthy WGSPreoperative treatment naïve NA 166 0.9626 CGPLH456 Healthy WGSPreoperative treatment naïve NA 168 0.9537 CGPLH457 Healthy WGSPreoperative treatment naïve NA 167 0.9429 CGPLH458 Healthy WGSPreoperative treatment naïve NA 167 0.9511 CGPLH459 Healthy WGSPreoperative treatment naïve NA 168 0.9609 CGPLH460 Healthy WGSPreoperative treatment naïve NA 168 0.9331 CGPLH463 Healthy WGSPreoperative treatment naïve NA 167 0.9506 CGPLH464 Healthy WGSPreoperative treatment naïve NA 170 0.9133 CGPLH465 Healthy WGSPreoperative treatment naïve NA 167 0.9251 CGPLH466 Healthy WGSPreoperative treatment naïve NA 167 0.9679 CGPLH467 Healthy WGSPreoperative treatment naïve NA 168 0.9273 CGPLH468 Healthy WGSPreoperative treatment naïve NA 167 0.8353 CGPLH469 Healthy WGSPreoperative treatment naïve NA 169 0.8225 CGPLH470 Healthy WGSPreoperative treatment naïve NA 168 0.9073 CGPLH471 Healthy WGSPreoperative treatment naïve NA 167 0.9354 CGPLH472 Healthy WGSPreoperative treatment naïve NA 166 0.8509 CGPLH473 Healthy WGSPreoperative treatment naïve NA 167 0.9206 CGPLH474 Healthy WGSPreoperative treatment naïve NA 168 0.8474 CGPLH475 Healthy WGSPreoperative treatment naïve NA 167 0.9155 CGPLH476 Healthy WGSPreoperative treatment naïve NA 169 0.8807 CGPLH477 Healthy WGSPreoperative treatment naïve NA 169 0.9129 CGPLH478 Healthy WGSPreoperative treatment naïve NA 167 0.9588 CGPLH479 Healthy WGSPreoperative treatment naïve NA 167 0.9303 CGPLH480 Healthy WGSPreoperative treatment naïve NA 169 0.9522 CGPLH481 Healthy WGSPreoperative treatment naïve NA 168 0.9558 CGPLH482 Healthy WGSPreoperative treatment naïve NA 168 0.9379 CGPLH483 Healthy WGSPreoperative treatment naïve NA 168 0.9518 CGPLH484 Healthy WGSPreoperative treatment naïve NA 166 0.9630 CGPLH485 Healthy WGSPreoperative treatment naïve NA 168 0.9547 CGPLH486 Healthy WGSPreoperative treatment naïve NA 169 0.9199 CGPLH487 Healthy WGSPreoperative treatment naïve NA 169 0.9575 CGPLH488 Healthy WGSPreoperative treatment naïve NA 167 0.9618 CGPLH490 Healthy WGSPreoperative treatment naïve NA 167 0.8950 CGPLH491 Healthy WGSPreoperative treatment naïve NA 168 0.9631 CGPLH492 Healthy WGSPreoperative treatment naïve NA 170 0.9335 CGPLH493 Healthy WGSPreoperative treatment naïve NA 168 0.8718 CGPLH494 Healthy WGSPreoperative treatment naïve NA 169 0.9623 CGPLH495 Healthy WGSPreoperative treatment naïve NA 166 0.8777 CGPLH496 Healthy WGSPreoperative treatment naïve NA 166 0.8788 CGPLH497 Healthy WGSPreoperative treatment naïve NA 167 0.9576 CGPLH498 Healthy WGSPreoperative treatment naïve NA 167 0.9526 CGPLH499 Healthy WGSPreoperative treatment naïve NA 167 0.9733 CGPLH500 Healthy WGSPreoperative treatment naïve NA 168 0.9542 CGPLH501 Healthy WGSPreoperative treatment naïve NA 169 0.9526 CGPLH052 Healthy WGSPreoperative treatment naïve NA 167 0.9512 CGPLH503 Healthy WGSPreoperative treatment naïve NA 169 0.8947 CGPLH504 Healthy WGSPreoperative treatment naïve NA 167 0.9561 CGPLH505 Healthy WGSPreoperative treatment naïve NA 166 0.9554 CGPLH506 Healthy WGSPreoperative treatment naïve NA 167 0.9733 CGPLH507 Healthy WGSPreoperative treatment naïve NA 168 0.9222 CGPLH508 Healthy WGSPreoperative treatment naïve NA 167 0.9674 CGPLH509 Healthy WGSPreoperative treatment naïve NA 167 0.9475 CGPLH510 Healthy WGSPreoperative treatment naïve NA 167 0.9459 CGPLH511 Healthy WGSPreoperative treatment naïve NA 168 0.9714 CGPLH512 Healthy WGSPreoperative treatment naïve NA 168 0.9442 CGPLH513 Healthy WGSPreoperative treatment naïve NA 166 0.9705 CGPLH514 Healthy WGSPreoperative treatment naïve NA 167 0.9690 CGPLH515 Healthy WGSPreoperative treatment naïve NA 167 0.9568 CGPLH516 Healthy WGSPreoperative treatment naïve NA 168 0.9508 CGPLH517 Healthy WGSPreoperative treatment naïve NA 168 0.9635 CGPLH518 Healthy WGSPreoperative treatment naïve NA 168 0.9647 CGPLH519 Healthy WGSPreoperative treatment naïve NA 166 0.9366 CGPLH520 Healthy WGSPreoperative treatment naïve NA 166 0.9649 CGPLH625 Healthy WGSPreoperative treatment naïve NA 166 0.8766 CGPLH626 Healthy WGSPreoperative treatment naïve NA 170 0.9011 CGPLH639 Healthy WGSPreoperative treatment naïve NA 165 0.9482 CGPLH640 Healthy WGSPreoperative treatment naïve NA 166 0.9131 CGPLH642 Healthy WGSPreoperative treatment naïve NA 167 0.9641 CGPLH643 Healthy WGSPreoperative treatment naïve NA 169 0.8450 CGPLH644 Healthy WGSPreoperative treatment naïve NA 170 0.9398 CGPLH646 Healthy WGSPreoperative treatment naïve NA 172 0.296 CGPLLU141 Lung Cancer TargetedMutation Analysis and WGS Preoperative treatment naïve II 164 0.8702CGPLLU161 Lung Cancer Targeted Mutation Analysis and WGS Preoperativetreatment naïve II 165 0.9128 CGPLLU162 Lung Cancer Targeted MutationAnalysis and WGS Preoperative treatment naïve II 165 0.7753 CGPLLUl63Lung Cancer Targeted Mutation Analysis and WGS Preoperative treatmentnaïve II 166 0.4770 CGPLLU168 Lung Cancer Targeted Mutation Analysis andWGS Preoperative treatment naïve I 163 0.9164 CGPLLU169 Lung CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1630.9326 CGPLLU176 Lung Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 168 0.9572 CGPLLU177 Lung Cancer TargetedMutation Analysis and WGS Preoperative treatment naïve II 166 0.8472CGPLLU203 Lung Cancer Targeted Mutation Analysis and WGS Preoperativetreatment naïve II 164 0.9119 CGPLLU205 Lung Cancer Targeted MutationAnalysis and WGS Preoperative treatment naïve II 163 0.9518 CGPLLU207Lung Cancer Targeted Mutation Analysis and WGS Preoperative treatmentnaïve II 166 0.9344 CGPLLU208 Lung Cancer Targeted Mutation Analysis andWGS Preoperative treatment naïve II 164 0.9091 CGPLOV11 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve V 1660.8902 CGPLOV12 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 167 0.8779 CGPLOV13 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve V 1660.7560 CGPLOV15 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve III 165 0.8585 CGPLOV16 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1650.9052 CGPLOV19 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 165 0.7854 CGPLOV20 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1650.8711 CGPLOV21 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve V 167 0.8942 CGPLOV22 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1640.8944 CGPLOV23 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 169 0.8510 CGPLOV24 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1660.9449 CGPLOV25 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 166 0.9590 CGPLOV26 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1610.8148 CGPLOV28 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 167 0.9635 CGPLOV31 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1670.9461 CGPLOV32 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 168 0.9582 CGPLOV37 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1700.9397 CGPLOV38 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 166 0.5779 CGPLOV40 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve V 1700.6097 CGPLOV41 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve V 167 0.9403 CGPLOV42 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1660.9265 CGPLOV43 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 167 0.9626 CGPLOV44 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1640.9536 CGPLOV46 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 166 0.9622 CGPLOV47 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve I 1650.9704 CGPLOV48 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 167 0.9675 CGPLOV49 Ovarian CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve III 1640.8998 CGPLOV50 Ovarian Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve III 165 0.9682 CGPLPA112 Pancreatic CancerWGS Preoperative treatment naïve II 164 0.8914 CGPLPA113 Doudenal CancerWGS Preoperative treatment naïve I 170 0.8751 CGPLPA114 Bile Duct CancerWGS Preoperative treatment naïve II 166 0.9098 CGPLPA115 Bile DuctCancer WGS Preoperative treatment naïve V 165 0.8053 CGPLPA117 Bile DuctCancer WGS Preoperative treatment naïve II 165 0.9395 CGPLPA118 BileDuct Cancer Targeted Mutation Analysis and WGS Preoperative treatmentnaïve I 167 0.9406 CGPLPA122 Bile Duct Cancer Targeted Mutation Analysisand WGS Preoperative treatment naïve II 164 0.8231 CGPLPA124 Bile DuctCancer Targeted Mutation Analysis and WGS Preoperative treatment naïveII 166 0.9108 CGPLPA125 Bile Duct Cancer WGS Preoperative treatmentnaïve II 166 0.9675 CGPLPA126 Bile Duct Cancer Targeted MutationAnalysis and WGS Preoperative treatment naïve II 166 0.9155 CGPLPA127Bile Duct Cancer WGS Preoperative treatment naïve V 167 0.8916 CGPLPA128Bile Duct Cancer Targeted Mutation Analysis and WGS Preoperativetreatment naïve II 167 0.9262 CGPLPA129 Bile Duct Cancer TargetedMutation Analysis and WGS Preoperative treatment naïve II 166 0.9220CGPLPA130 Bile Duct Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 169 0.8586 CGPLPA131 Bile Duct CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1650.7707 CGPLPA134 Bile Duct Cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 160 0.7502 CGPLPA135 Bile Duct CancerWGS Preoperative treatment naïve I 165 0.9495 CGPLPA136 Bile Duct CancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1640.9289 CGPLPA137 Bile Duct Cancer WGS Preoperative treatment naïve II166 0.9588 CGPLPA139 Bile Duct Cancer WGS Preoperative treatment naïve V166 0.9511 CGPLPA14 Pancreatic Cancer WGS Preoperative treatment naïveII 167 0.8718 CGPLPA140 Bile Duct Cancer Targeted Mutation Analysis andWGS Preoperative treatment naïve II 166 0.9215 CGPLPA141 Bile DuctCancer WGS Preoperative treatment naïve II 165 0.9172 CGPLPA15Pancreatic Cancer WGS Preoperative treatment naïve II 167 0.9111CGPLPA155 Bile Duct Cancer WGS Preoperative treatment naïve II 1650.9496 CGPLPA156 Pancreatic Cancer WGS Preoperative treatment naïve II167 0.9479 CCPLPA165 Bile Duct Cancer WGS Preoperative treatment naïve I168 0.9596 CGPLPA168 Bile Duct Cancer WGS Preoperative treatment naïveII 162 0.7838 CGPLPA17 Pancreatic Cancer WGS Preoperative treatmentnaïve II 166 0.8624 CGPLPA184 Bile Duct Cancer WGS Preoperativetreatment naïve II 165 0.9100 CGPLPA187 Bile Duct Cancer WGSPreoperative treatment naïve II 165 0.8577 CGPLPA23 Pancreatic CancerWGS Preoperative treatment naïve II 165 0.7887 CGPLPA25 PancreaticCancer WGS Preoperative treatment naïve II 166 0.9549 CGPLPA26Pancreatic Cancer WGS Preoperative treatment naïve II 166 0.9598CGPLPA28 Pancreatic Cancer WGS Preoperative treatment naïve II 1650.9069 CGPLPA33 Pancreatic Cancer WGS Preoperative treatment naïve II166 0.8361 CGPLPA34 Pancreatic Cancer WGS Preoperative treatment naïveII 168 0.8946 CGPLPA37 Pancreatic Cancer WGS Preoperative treatmentnaïve II 165 0.8840 CGPLPA38 Pancreatic Cancer WGS Preoperativetreatment naïve II 167 0.8746 CGPLPA39 Pancreatic Cancer WGSPreoperative treatment naïve II 167 0.8562 CGPLPA40 Pancreatic CancerWGS Preoperative treatment naïve II 165 0.8563 CGPLPA42 PancreaticCancer WGS Preoperative treatment naïve II 167 0.9126 CGPLPA46Pancreatic Cancer WGS Preoperative treatment naïve II 169 0.8274CGPLPA47 Pancreatic Cancer WGS Preoperative treatment naïve II 1660.8376 CGPLPA48 Pancreatic Cancer WGS Preoperative treatment naïve I 1670.9391 CGPLPA52 Pancreatic Cancer WGS Preoperative treatment naïve II167 0.9452 CGPLPA53 Pancreatic Cancer WGS Preoperative treatment naïve I163 0.9175 CGPLPA58 Pancreatic Cancer WGS Preoperative treatment naïveII 165 0.9587 CGPLPA59 Pancreatic Cancer WGS Preoperative treatmentnaïve II 163 0.9230 CGPLPA67 Pancreatic Cancer WGS Preoperativetreatment naïve II 166 0.9574 CGPLPA69 Pancreatic Cancer WGSPreoperative treatment naïve I 168 0.9172 CGPLPA71 Pancreatic Cancer WGSPreoperative treatment naïve II 167 0.9424 CGPLPA74 Pancreatic CancerWGS Preoperative treatment naïve II 166 0.9688 CGPLPA76 PancreaticCancer WGS Preoperative treatment naïve II 163 0.9681 CGPLPA85Pancreatic Cancer WGS Preoperative treatment naïve II 165 0.9137CGPLPA86 Pancreatic Cancer WGS Preoperative treatment naïve II 1650.8875 CGPLPA92 Pancreatic Cancer WGS Preoperative treatment naïve II167 0.9389 CGPLPA93 Pancreatic Cancer WGS Preoperative treatment naïveII 166 0.8585 CGPLPA94 Pancreatic Cancer WGS Preoperative treatmentnaïve II 162 0.9365 CGPLPA95 Pancreatic Cancer WGS Preoperativetreatment naïve II 163 0.8542 CGST102 Gastric cancer Targeted MutationAnalysis and WGS Preoperative treatment naïve II 167 0.9496 CGST11Gastric cancer WGS Preoperative treatment naïve IV 169 0.9419 CGST110Gastric cancer Targeted Mutation Analysis and WGS Preoperative treatmentnaïve II 167 0.9626 CGST114 Gastric cancer Targeted Mutation Analysisand WGS Preoperative treatment naïve II 164 0.9535 CGST13 Gastric cancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1660.9369 CGST131 Gastric cancer WGS Preoperative treatment naïve II 1710.9428 CGST141 Gastric cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 168 0.9621 CGST16 Gastric cancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1660.7804 CGST18 Gastric cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 169 0.9523 CGST21 Gastric cancer WGSPreoperative treatment naïve II 165 −0.4778  CGST26 Gastric cancer WGSPreoperative treatment naïve IV 166 0.9554 CGST28 Gastric cancerTargeted Mutation Analysis and WGS Preoperative treatment naïve X 1690.9076 CGST30 Gastric cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve II 169 0.9246 CGST32 Gastric cancerTargeted Mutation Analysis and WGS Preoperative treatment naïve II 1690.9431 CGST33 Gastric cancer Targeted Mutation Analysis and WGSPreoperative treatment naïve I 168 0.7999 CGST38 Gastric cancer WGSPreoperative treatment naïve 0 168 0.9368 CGST39 Gastric cancer TargetedMutation Analysis and WGS Preoperative treatment naïve IV 164 0.8742CGST41 Gastric cancer Targeted Mutation Analysis and WGS Preoperativetreatment naïve IV 168 0.8194 CGST45 Gastric cancer Targeted MutationAnalysis and WGS Preoperative treatment naïve II 168 0.9576 CGST47Gastric cancer Targeted Mutation Analysis and WGS Preoperative treatmentnaïve I 168 0.9641 CGST48 Gastric cancer Targeted Mutation Analysis andWGS Preoperative treatment naïve IV 167 0.7469 CGST53 Gastric cancer WGSPreoperative treatment naïve 0 173 0.0019 CGST58 Gastric cancer TargetedMutation Analysis and WGS Preoperative treatment naïve II 169 0.9470CGST67 Gastric cancer WGS Preoperative treatment naïve I 170 0.9352CGST77 Gastric cancer WGS Preoperative treatment naïve IV 170 0.0043CGST80 Gastric cancer Targeted Mutation Analysis and WGS Preoperativetreatment naïve II 168 0.9313 CGST81 Gastric cancer Targeted MutationAnalysis and WGS Preoperative treatment naïve I 168 0.9480 Correlationof GC Corrected Fragment Ratio Profile to Mutant Median Alelle FragmentFraction Detected Detected Fraction Ratio of Reads using using DetectedProfile Mapped to DELFI DELFI using of Healthy Mitochondrial DELFI (95%(98% Targeted Patient Individuals Genome Score specificity) specificity)sequencing* CGCRC291 0.5268 0.0484% 0.9976 Y Y 22.85% CGCRC292 0.8835 00270% 0.7299 Y N  1.41% CGCRC293 0.9206 0.0748% 0.5234 N N  3.35%CGCRC294 0.8904 0.0135% 0.8757 Y Y  0.17% CGCRC296 0.8395 0.0369% 0.9951Y Y ND CGCRC299 0.9268 0.0392% 0.9648 Y Y ND CGCRC300 0.9303 0.0235%0.4447 N N ND CGCRC301 0.9151 0.0310% 0.2190 N N  3.21% CGCRC302 0.92430.0112% 0.9897 Y Y  3.12% CGCRC304 0.9360 0.0093% 0.9358 Y Y  3.27%CGCRC305 0.9250 0 0120% 0.8988 Y Y  3.19% CGCRC306 0.8186 0.0781% 0.9466Y Y  8.02% CGCRC307 0.9342 0.0781% 0.7042 Y N  0.56% CGCRC308 0.93240.0078% 0.9082 Y Y  0.11% CGCRC311 0.9156 0.0173% 0.1867 N N ND CGCRC3150.8846 0.0241% 0.6422 Y N  0.27% CGCRC316 0.5879 0.0315% 0.9971 Y Y 5.52% CGCRC317 0.8944 0.0184% 0.9855 Y Y  0.36% CGCRC318 0.9140 0.0156%0.5615 N N ND CGCRC319 0.8230 0.1259% 0.9925 Y Y  0.11% CGCRC320 0.91010.0383% 0.8019 Y Y  0.64% CGCRC321 0.9091 0.0829% 0.9759 Y Y  3.20%CGCRC333 0.4355 0.4264% 0.9974 Y Y 43.03% CGCRC335 0.6858 0.1154% 0.9887Y Y 81.61% CGCRC338 0.7573 0.1436% 0.9976 Y Y 36.00% CGCRC341 0.91810.0197% 0.9670 Y Y ND CGCRC342 0.1845 0.1732% 0.9987 Y Y 30.72%CGPLBR100 0.8946 0.1234% 0.8664 Y Y ND CGPLBR101 0.9304 0.0709% 0.9385 YY ND CGPLBR102 0.9345 0.4742% 0.9052 Y Y  0.25% CGPLBR103 0.9251 0.0775%0.5994 N N ND CGPLBR104 0.9192 0.0532% 0.9950 Y Y  0.13% CGPLBR12 0.77600.1407% 0.7598 Y Y — CGPLBR18 0.9534 0.0267% 0.3886 N N — CGPLBR230.9312 0.0144% 0.1235 N N — CGPLBR24 0.8766 0.0210% 0.7480 Y Y —CGPLBR28 0.8120 0.1456% 0.9630 Y Y — CGPLBR30 0.6611 0.0952% 0.9956 Y Y— CGPLBR31 0.9556 0.0427% 0.2227 N N — CGPLBR32 0.9229 0.0308% 0.9815 YY — CGPLBR33 0.9432 0.0617% 0.2863 N N — CGPLBR34 0.9425 0.0115% 0.1637N N — CGPLBR35 0.9348 0.1371% 0.5057 N N — CGPLBR36 0.8884 0.0813%0.4017 N N — CGPLBR37 0.9496 0.0518% 0.0314 N N — CGPLBR38 0.03490.1352% 0.8983 Y Y  0.53% CGPLBR40 0.9244 0.0929% 0.9046 Y Y ND CGPLBR410.9346 0.0544% 0.9416 Y Y  0.32% CGPLBR45 0.9285 0.0296% 0.3860 N N —CGPLBR46 0.9005 0.0345% 0.7270 Y N — CGPLBR47 0.9028 0.0591% 0.6247 Y Y— CGPLBR48 0.8246 0.0504% 0.9973 Y Y  0.18% CGPLBR49 0.7887 0.0377%0.9946 Y Y ND CGPLBR50 0.9332 0.0137% 0.6820 Y N — CGPLBR51 0.91600.0863% 0.6915 Y N — CGPLBR52 0.9196 0.0165% 0.6390 Y N — CGPLBR550.9341 0.0356% 0.9494 Y Y  0.68% CGPLBR56 0.9428 0.2025% 0.4700 N N —CGPLBR57 0.9416 0.0902% 0.9090 Y Y ND CGPLBR59 0.9130 0.0761% 0.5828 N NND CGPLBR60 0.8916 0.0626% 0.8779 Y Y — CGPLBR61 0.9422 0.0601% 0.4417 NN  0.44% CGPLBR63 0.9132 0.0514% 0.8788 Y Y ND CGPLBR65 0.8970 0.0264%0.9048 Y Y — CGPLBR68 0.9532 0.0164% 0.7883 Y Y ND CGPLBR69 0.94740.0279% 0.0600 N N ND CGPLBR70 0.9388 0.0171% 0.6447 Y N  0.36% CGPLBR710.9368 0.0271% 0.6706 Y N  0.10% CGPLBR72 0.9640 0.0263% 0.6129 N N NDCGPLBR73 0.9421 0.0142% 0.0746 N N  0.27% CGPLBR76 0.9254 0.0775% 0.9334Y Y  0.12% CGPLBR81 0.8193 0.0241% 0.9899 Y Y — CGPLBR82 0.9288 0.1640%0.9834 Y Y  0.12% CGPLBR83 0.9138 0.0419% 0.9810 Y Y  0.28% CGPLBR840.8659 0.0274% 0.9901 Y Y — CGPLBR87 0.8797 0.0294% 0.9968 Y Y  0.45%CGPLBR88 0.8547 0.0181% 0.9958 Y Y  0.38% CGPLBR90 0.8330 0.0417% 0.9667Y Y — CGPLBR91 0.9408 0.0799% 0.8710 Y Y ND CGPLBR92 0.8835 0.1042%0.9856 Y Y  0.20% CGPLBR93 0.9072 0.0352% 0.7253 Y N ND CGPLH189 0.89470.0591% 0.1748 N N — CGPLH190 0.9369 0.1193% 0.5168 N N — CGPLH1920.9487 0.0276% 0.0178 N N — CGPLH193 0.9442 0.0420% 0.5794 N N —CGPLH194 0.9289 0.0407% 0.1616 N N — CGPLH196 0.9512 0.0266% 0.0999 N N— CGPLH197 0.9416 0.0334% 0.4699 N N — CGPLH198 0.9457 0.0302% 0.6571 YN — CGPLH199 0.9439 0.0170% 0.5584 N N — CGPLH200 0.9391 0.0362% 0.3833N N — CGPLH201 0.9180 0.0470% 0.8395 Y Y — CGPLH202 0.9436 0.0501%0.1088 N N — CGPLH203 0.9575 0.0455% 0.2485 N N — CGPLH205 0.92830.0409% 0.4401 N N — CGPLH208 0.9409 0.0371% 0.2706 N N — CGPLH2090.9367 0.0427% 0.2213 N N — CGPLH210 0.9181 0.0279% 0.3500 N N —CGPLH211 0.9410 0.0317% 0.1752 N N — CGPLH300 0.9200 0.0397% 0.0226 N N— CGPLH307 0.9167 0.0388% 0.1789 N N — CGPLH308 0.8352 0.0311% 0.0155 NN — CGPLH309 0.9451 0.0226% 0.0441 N N — CGPLH310 0.9527 0.0145% 0.7135Y N — CGPLH311 0.9348 0.0202% 0.2589 N N — CGPLH314 0.9491 0.0212%0.1632 N N — CGPLH315 0.9427 0.0071% 0.3450 N N — CGPLH316 0.95520.0191% 0.4697 N N — CGPLH317 0.9352 0 0232% 0.4330 N N — CGPLH3190.9189 0.0263% 0.2232 N N — CGPLH320 0.9165 0.0222% 0.1095 N N —CGPLH322 0.9411 0.0248% 0.0749 N N — CGPLH324 0.9133 0.0402% 0.0128 N N— CGPLH325 0.9202 0.0711% 0.0102 N N — CGPLH326 0.9408 0.0213% 0.0475 NN — CGPLH327 0.9071 0.1275% 0.4891 N N — CGPLH328 0.9332 0.0256% 0.0234N N — CGPLH329 0.8396 0.0269% 0.0139 N N — CGPLH330 0.9403 0.0203%0.2642 N N — CGPLH331 0.9377 0.0314% 0.0304 N N — CGPLH333 0.91320.0350% 0.1633 N N — CGPLH335 0.9333 0.0285% 0.0096 N N — CGPLH3360.9159 0.0158% 0.3872 N N — CGPLH337 0.9262 0.0367% 0.2976 N N —CGPLH338 0.9303 0.0103% 0.0431 N N — CGPLH339 0.9338 0.0280% 0.0379 N N— CGPLH340 0.9321 0.0210% 0.0379 N N — CGPLH341 0.9187 0.0448% 0.1775 NN — CGPLH342 0.8986 0.0283% 0.0904 N N — CGPLH343 0.9067 0.0632% 0.0160N N — CGPLH344 0.8998 0.0257% 0.0120 N N — CGPLH345 0.9107 0.0445%0.0031 N N — CGPLH346 0.9074 0.0208% 0.0686 N N — CGPLH350 0.93880.0284% 0.0071 N N — CGPLH351 0.9294 0.0223% 0.0207 N N — CGPLH3520.9190 0.0613% 0.0512 N N — CGPLH353 0.9130 0.0408% 0.0132 N N —CGPLH354 0.9121 0.0318% 0.0082 N N — CGPLH355 0.9308 0.0400% 0.6407 Y N— CGPLH356 0.8312 0.0427% 0.2437 N N — CGPLH357 0.9540 0.0217% 0.0070 NN — CGPLH358 0.9372 0.0174% 0.1451 N N — CGPLH360 0.8775 0.0395% 0.0048N N — CGPLH361 0.9283 0.0268% 0.1524 N N — CGPLH362 0.9503 0.0309%0.4832 N N — CGPLH363 0.9187 0.0620% 0.0199 N N — CGPLH364 0.94800.0282% 0.8719 Y Y — CGPLH365 0.9051 0.1740% 0.9638 Y Y — CGPLH3660.9170 0.0344% 0.0952 N N — CGPLH367 0.9181 0.0353% 0.1235 N N —CGPLH368 0.9076 0.1073% 0.1252 N N — CGPLH369 0.9541 0.0246% 0.2821 N N— CGPLH370 0.9423 0.0410% 0.0989 N N — CGPLH371 0.9414 0.0734% 0.2173 NN — CGPLH380 0.9424 0.0523% 0.0128 N N — CGPLH381 0.9501 0.0435% 0.0152N N — CGPLH382 0.9584 0.0340% 0.0326 N N — CGPLH383 0.9407 0.0389%0.0035 N N — CGPLH384 0.9043 0.0207% 0.0258 N N — CGPLH385 0.92460.0165% 0.0566 N N — CGPLH386 0.8859 0.0502% 0.2677 N N — CGPLH3870.9223 0.0375% 0.0081 N N — CGPLH388 0.9266 0.0527% 0.0499 N N —CGPLH389 0.9035 0.0667% 0.6585 Y N — CGPLH390 0.9182 0.0229% 0.0837 N N— CGPLH391 0.9162 0.0223% 0.0716 N N — CGPLH392 0.9014 0.0424% 0.1305 NN — CGPLH393 0.9045 0.0407% 0.0037 N N — CGPLH394 0.9292 0.0522% 0.1073N N — CGPLH395 0.9254 0.0424% 0.0171 N N — CGPLH396 0.8928 0.0393%0.0303 N N — CGPLH398 0.9578 0.0242% 0.3195 N N — CGPLH399 0.91950.0579% 0.0685 N N — CGPLH400 0.9047 0.0300% 0.2103 N N — CGPLH4010.9339 0.0146% 0.0620 N N — CGPLH402 0.8800 0.1516% 0.0395 N N —CGPLH403 0.8829 0.0515% 0.0223 N N — CGPLH404 0.8948 0.0528% 0.0027 N N— CGPLH405 0.9204 0.0358% 0.0188 N N — CGPLH406 0.8592 0.0667% 0.0206 NN — CGPLH407 0.9099 0.0229% 0.0040 N N — CGPLH408 0.9192 0.0415% 0.1257N N — CGPLH409 0.8950 0.0302% 0.0056 N N — CGPLH410 0.9006 0.0453%0.0019 N N — CGPLH411 0.8857 0.0621% 0.0188 N N — CGPLH412 0.91910.0140% 0.0417 N N — CGPLH413 0.9145 0.0355% 0.0084 N N — CGPLH4140.9127 0.0290% 0.0294 N N — CGPLH415 0.9025 0.0296% 0.0131 N N —CGPLH416 0.9388 0.0198% 0.0645 N N — CGPLH417 0.9192 0.0241% 0.0836 N N— CGPLH418 0.9234 0.0306% 0.0052 N N — CGPLH419 0.9295 0.0280% 0.0489 NN — CGPLH420 0.9109 0.0187% 0.0420 N N — CGPLH422 0.9006 0.0208% 0.0324N N — CGPLH423 0.8288 0.0532% 0.0139 N N — CGPLH424 0.9265 0.1119%0.0864 N N — CGPLH425 0.9488 0.0722% 0.0156 N N — CGPLH426 0.90800.0548% 0.1075 N N — CGPLH427 0.9257 0.0182% 0.0470 N N — CGPLH4280.9272 0.0346% 0.0182 N N — CGPLH429 0.8757 0.0593% 0.8143 Y Y —CGPLH430 0.9307 0.0258% 0.0389 N N — CGPLH431 0.9185 0.0234% 0.0174 N N— CGPLH432 0.9082 0.0433% 0.0181 N N — CGPLH434 0.9442 0.0297% 0.0050 NN — CGPLH435 0.9097 0.0179% 0.0441 N N — CGPLH436 0.9158 0.0290% 0.0958N N — CGPLH437 0.9245 0.0156% 0.0136 N N — CGPLH438 0.9138 0.0169%0.1041 N N — CGPLH439 0.9028 0.0226% 0.0078 N N — CGPLH440 0.82950.0330% 0.0687 N N — CGPLH441 0.9430 0.0178% 0.0085 N N — CGPLH4420.9405 0.0169% 0.0582 N N — CGPLH443 0.8801 0.0207% 0.0578 N N —CGPLH444 0.8068 0.0464% 0.0097 N N — CGPLH445 0.8750 0.0267% 0.1939 N N— CGPLH446 0.9257 0.0281% 0.0340 N N — CGPLH447 0.8968 0.0167% 0.0017 NN — CGPLH448 0.9191 0.0401% 0.0389 N N — CGPLH449 0.9254 0.0236% 0.0116N N — CGPLH450 0.9195 0.0331% 0.0597 N N — CGPLH451 0.9167 0.0262%0.0104 N N — CGPLH452 0.8948 0.0480% 0.4722 N N — CGPLH453 0.93390.0186% 0.3419 N N — CGPLH455 0.9322 0.0455% 0.4536 N N — CGPLH4560.9098 0.0207% 0.0385 N N — CGPLH457 0.9022 0.0298% 0.0384 N N —CGPLH458 0.9275 0.0298% 0.1891 N N — CGPLH459 0.9209 0.0281% 0.0371 N N— CGPLH460 0.8863 0.0227% 0.1157 N N — CGPLH463 0.9372 0.0130% 0.0865 NN — CGPLH464 0.8511 0.0659% 0.2040 N N — CGPLH465 0.9164 0.0325% 0.0124N N — CGPLH466 0.9408 0.0155% 0.1733 N N — CGPLH467 0.9024 0.0229%0.2303 N N — CGPLH468 0.9345 0.0247% 0.5427 N N — CGPLH469 0.87990.0201% 0.5351 N N — CGPLH470 0.9228 0.0715% 0.0327 N N — CGPLH4710.9333 0.0150% 0.0406 N N — CGPLH472 0.8915 0.0481% 0.6152 N N —CGPLH473 0.9128 0.0443% 0.2995 N N — CGPLH474 0.9245 0.0316% 0.8246 Y N— CGPLH475 0.9233 0.0269% 0.0736 N N — CGPLH476 0.9059 0.0236% 0.0143 NN — CGPLH477 0.9376 0.0382% 0.1111 N N — CGPLH478 0.9344 0.0256% 0.0628N N — CGPLH479 0.9207 0.0221% 0.0648 N N — CGPLH480 0.9046 0.0672%0.7473 Y N — CGPLH481 0.9113 0.0311% 0.0282 N N — CGPLH482 0.93360.0162% 0.0058 N N — CGPLH483 0.9275 0.0251% 0.0495 N N — CGPLH4840.9366 0.0261% 0.0048 N N — CGPLH485 0.9128 0.0291% 0.1084 N N —CGPLH486 0.9042 0.0220% 0.0820 N N — CGPLH487 0.9098 0.0594% 0.2154 N N— CGPLH488 0.8299 0.0409% 0.0903 N N — CGPLH490 0.8794 0.0432% 0.0424 NN — CGPLH491 0.8332 0.0144% 0.0223 N N — CGPLH492 0.8799 0.0322% 0.0311N N — CGPLH493 0.9330 0.0065% 0.0280 N N — CGPLH494 0.9303 0.0232%0.0824 N N — CGPLH495 0.8908 0.0513% 0.0465 N N — CGPLH496 0.83980.0208% 0.0572 N N — CGPLH497 0.9330 0.0335% 0.0404 N N — CGPLH4980.9315 0.0403% 0.0752 N N — CGPLH499 0.9442 0.0198% 0.0149 N N —CGPLH500 0.9240 0.0433% 0.0754 N N — CGPLH501 0.9308 0.0300% 0.0159 N N— CGPLH052 0.9200 0.0351% 0.0841 N N — CGPLH503 0.8939 0.0398% 0.0649 NN — CGPLH504 0.9324 0.0440% 0.1231 N N — CGPLH505 0.9243 0.0605% 0.1869N N — CGPLH506 0.9498 0.0284% 0.0180 N N — CGPLH507 0.9192 0.0186%0.0848 N N — CGPLH508 0.9410 0.0150% 0.1077 N N — CGPLH509 0.93230.0163% 0.0828 N N — CGPLH510 0.9548 0.0128% 0.0376 N N — CGPLH5110.9493 0.0224% 0.1779 N N — CGPLH512 0.9244 0.0094% 0.0076 N N —CGPLH513 0.9595 0.0441% 0.5250 N N — CGPLH514 0.9369 0.0114% 0.3131 N N— CGPLH515 0.9283 0.0352% 0.4936 N N — CGPLH516 0.8298 0.0175% 0.0916 NN — CGPLH517 0.9494 0.0161% 0.0059 N N — CGPLH518 0.9432 0.0274% 0.0130N N — CGPLH519 0.9351 0.0171% 0.0949 N N — CGPLH520 0.9476 0.0241%0.0844 N N — CGPLH625 0.9231 0.0697% 0.4977 N N — CGPLH626 0.92690.0231% 0.3100 N N — CGPLH639 0.9410 0.0549% 0.0773 N N — CGPLH6400.9264 0.0232% 0.0327 N N — CGPLH642 0.8376 0.0768% 0.0555 N N —CGPLH643 0.9271 0.0579% 0.1325 N N — CGPLH644 0.8948 0.0621% 0.3819 N N— CGPLH646 0.8691 0.0462% 0.2423 N N — CGPLLU144 0.6861 0.0423% 0.9892 YY  5.10% CGPLLU161 0.9187 0.0273% 0.9955 Y Y  0.20% CGPLLU162 0.08360.1410% 0.9966 Y Y  0.22% CGPLLUl63 0.3033 0.0724% 0.9940 Y Y  0.21%CGPLLU168 0.6842 0.0712% 0.9861 Y Y  0.07% CGPLLU169 0.9189 0.0846%0.9856 Y Y  0.13% CGPLLU176 0.9081 0.0626% 0.8769 Y Y ND CGPLLU1770.6790 0.0564% 0.9924 Y Y  3.22% CGPLLU203 0.8741 0.0568% 0.9178 Y Y 0.11% CGPLLU205 0.9476 0.0495% 0.9877 Y Y ND CGPLLU207 0.9379 0.0421%0.9908 Y Y  0.32% CGPLLU208 0.8942 0.0815% 0.9273 Y Y  1.33% CGPLOV110.8872 0.0469% 0.9343 Y Y  0.87% CGPLOV12 0.8973 0.2767% 0.9764 Y Y NDCGPLOV13 0.9146 0.1017% 0.9690 Y Y  0.35% CGPLOV15 0.8552 0.0876% 0.9945Y Y  3.54% CGPLOV16 0.9046 0.0400% 0.9683 Y Y  1.12% CGPLOV19 0.75780.1089% 0.9989 Y Y 46.35% CGPLOV20 0.9154 0.0581% 0.9749 Y Y  0.21%CGPLOV21 0.8889 0.0677% 0.9961 Y Y 14.36% CGPLOV22 0.9355 0.0251% 0.9775Y Y  0.49% CGPLOV23 0.8850 0.1520% 0.9910 Y Y  1.39% CGPLOV24 0.89950.0303% 0.9856 Y Y ND CGPLOV25 0.9228 0.0141% 0.8544 Y Y ND CGPLOV260.9351 0.0646% 0.9946 Y Y ND CGPLOV28 0.9378 0.0547% 0.8160 Y Y NDCGPLOV31 0.9283 0.1605% 0.9795 Y Y ND CGPLOV32 0.9338 0.1351% 0.8609 Y YND CGPLOV37 0.8831 0.0985% 0.9849 Y Y  0.29% CGPLOV38 0.6502 0.0490%0.9990 Y Y  4.89% CGPLOV40 0.8127 0.6145% 0.9963 Y Y  6.73% CGPLOV410.8929 0.1110% 0.9484 Y Y  0.60% CGPLOV42 0.9086 0.0489% 0.9979 Y Y 1.24% CGPLOV43 0.9342 0.0432% 0.6042 N N ND CGPLOV44 0.9173 0.1946%0.9962 Y Y  0.37% CGPLOV46 0.9291 0.0801% 0.9128 Y Y ND CGPLOV47 0.94610.0270% 0.3410 N N  3.20% CGPLOV48 0.9429 0.0422% 0.4874 N N 10.70%CGPLOV49 0.8083 0.1527% 0.9897 Y Y  2.03% CGPLOV50 0.9382 0.0907% 0.9955Y Y ND CGPLPA112 0.9429 0.0268% 0.0856 N N — CGPLPA113 0.7674 1.0116%0.9935 Y Y — CGPLPA114 0.9246 0.0836% 0.7598 Y Y — CGPLPA115 0.88100.0763% 0.9974 Y Y — CGPLPA117 0.8767 0.1084% 0.9049 Y Y — CGPLPA1180.9001 0.1842% 0.9859 Y Y  0.14% CGPLPA122 0.8058 0.2047% 0.9983 Y Y37.22% CGPLPA124 0.9238 0.1542% 0.8791 Y Y  0.62% CGPLPA125 0.93730.0273% 0.0228 N N — CGPLPA126 0.9139 0.4349% 0.9908 Y Y ND CGPLPA1270.8117 0.4371% 0.9789 Y Y — CGPLPA128 0.9003 0.1317% 0.9812 Y Y NDCGPLPA129 0.9155 0.0642% 0.9839 Y Y ND CGPLPA130 0.8499 0.1055% 0.9895 YY ND CGPLPA131 0.9195 0.0760% 0.9685 Y Y  0.21% CGPLPA134 0.8847 0.0260%0.9896 Y Y  0.93% CGPLPA135 0.9184 0.0558% 0.6594 Y N — CGPLPA136 0.90500.0769% 0.9596 Y Y  0.10% CGPLPA137 0.9320 0.0499% 0.7282 Y N —CGPLPA139 0.9374 0.0465% 0.0743 N N — CGPLPA14 0.9069 0.0515% 0.9824 Y Y— CGPLPA140 0.9548 0.0330% 0.9751 Y Y  3.21% CGPLPA141 0.9381 0.0920%0.9388 Y Y — CGPLPA15 0.8927 0.0160% 0.8737 Y Y — CGPLPA155 0.93130.0260% 0.8013 Y Y — CGPLPA156 0.9432 0.0290% 0.0159 N N — CCPLPA1650.9309 0.0558% 0.2158 N N — CGPLPA168 0.7757 0.3123% 0.9878 Y Y —CGPLPA17 0.6771 1.2600% 0.9956 Y Y — CGPLPA184 0.9203 0.0897% 0.9926 Y Y— CGPLPA187 0.8968 0.0658% 0.9875 Y Y — CGPLPA23 0.6938 0.5785% 0.9984 YY — CGPLPA25 0.9239 0.0380% 0.8103 Y Y — CGPLPA26 0.9356 0.0247% 0.8231Y Y — CGPLPA28 0.8930 0.0546% 0.9036 Y Y — CGPLPA33 0.8553 0.0894%0.9967 Y Y — CGPLPA34 0.8885 0.0438% 0.7977 Y Y — CGPLPA37 0.92940.0410% 0.9924 Y Y — CGPLPA38 0.8941 0.0372% 0.9851 Y Y — CGPLPA390.7972 0.5058% 0.9951 Y Y — CGPLPA40 0.8865 0.2268% 0.9920 Y Y —CGPLPA42 0.8863 0.0283% 0.3544 N N — CGPLPA46 0.7525 1.0982% 0.9952 Y Y— CGPLPA47 0.8439 0.1598% 0.9946 Y Y — CGPLPA48 0.9207 1.0232% 0.2251 NN — CGPLPA52 0.8863 0.0154% 0.0963 N N — CGPLPA53 0.8776 0.1824% 0.8946Y Y — CGPLPA58 0.9224 0.0803% 0.9056 Y Y — CGPLPA59 0.9193 0.1479%0.9759 Y Y — CGPLPA67 0.9248 0.0329% 0.6716 Y N — CGPLPA69 0.85920.0458% 0.1245 Y Y — CGPLPA71 0.8888 0.0479% 0.0524 Y Y — CGPLPA740.9372 0.0292% 0.0108 Y Y — CGPLPA76 0.9441 0.0345% 0.0897 Y Y —CGPLPA85 0.9337 0.0363% 0.0508 Y Y — CGPLPA86 0.8042 0.7564% 0.9864 Y Y— CGPLPA92 0.9003 0.1458% 0.7061 N N — CGPLPA93 0.8023 0.6250% 0.9978 YY — CGPLPA94 0.9433 0.0180% 0.9025 Y Y — CGPLPA95 0.8571 0.0815% 0.9941Y Y — CGST102 0.9057 0.0704% 0.8581 Y Y  0.43% CGST11 0.9161 0.0651%0.1435 N N — CGST110 0.9232 0.0817% 0.8900 Y Y ND CGST114 0.9038 0.0317%0.5893 N N ND CGST13 0.9156 0.0321% 0.9754 Y Y ND CGST131 0.8886 0.2752%0.9409 Y Y — CGST141 0.9205 0.0388% 0.2008 N N ND CGST16 0.8355 0.1744%0.9974 Y Y  0.93% CGST18 0.9111 0.0298% 0.3842 N N  0.14% CGST21 0.26870.2295% 0.9910 Y Y — CGST26 0.9140 0.0399% 0.5009 N N — CGST28 0.78320.1295% 0.9955 Y Y  1.62% CGST30 0.9121 0.0338% 0.9183 Y Y  0.42% CGST320.8639 0.0247% 0.9512 Y Y  2.99% CGST33 0.7770 0.0798% 0.9805 Y Y  2.32%CGST38 0.8758 0.0540% 0.9416 Y Y — CGST39 0.9401 0.0287% 0.8480 Y Y NDCGST41 0.9284 0.0398% 0.9253 Y Y ND CGST45 0.9036 0.0220% 0.9713 Y Y NDCGST47 0.9096 0.0157% 0.9687 Y Y  0.45% CGST48 0.5445 0.0220% 0.9975 Y Y 4.21% CGST53 0.7888 0.1140% 0.9914 Y Y — CGST58 0.9094 0.0696% 0.9705 YY ND CGST67 0.8853 0.3245% 0.9002 Y Y — CGST77 0.8295 0.1851% 0.9981 Y Y— CGST80 0.8845 0.0490% 0.9513 Y Y  1.04% CGST81 0.8851 0.0138% 0.9748 YY  0.21% *NO indicates not detected. please see reference 10 foradditional information on targeted sequencing analyes. DELFI cancerdetection at 95% and 98% specificity is based on scores greater than0.6200 and 0.7500 respectively.

1-67. (canceled)
 68. A system for determining a cell free DNA (cfDNA)fragmentation profile of a subject comprising: processing cfDNAfragments obtained from a sample obtained from the subject intosequencing libraries; subjecting the sequencing libraries to wholegenome sequencing to obtain sequenced fragments, wherein genome coverageis from about 0.1× to 9×; mapping the sequenced fragments to a genome toobtain genomic intervals of mapped sequences; analyzing the genomicintervals of mapped sequences to determine cfDNA fragment lengths; anddetermining a cfDNA fragmentation profile for the subject.
 69. Thesystem of claim 68, wherein the system is a machine learning system. 70.The system of claim 69, wherein the machine learning system is agradient tree boosting machine learning system.
 71. The system of claim68, wherein a cfDNA fragmentation profile in the subject that is morevariable than a reference cfDNA fragmentation profile is indicative ofthe subject as having or at risk of having cancer.
 72. The system ofclaim 68, wherein a cfDNA fragmentation profile in the subject that isless or equally variable than a reference cfDNA fragmentation profile isindicative of the subject as being healthy.
 73. The system of claim 71,wherein the reference cfDNA fragmentation profile is a referencenucleosome cfDNA fragmentation profile.
 74. The system of claim 68,wherein determining the cfDNA fragmentation profile distinguishescirculating tumor DNA (ctDNA) from non-cancer-associated white bloodcell DNA in the blood.
 75. The system of claim 68, wherein the mappedsequences comprise tens or hundreds to thousands of genomic intervals.76. The system of claim 68, wherein the genomic intervals arenon-overlapping.
 77. The system of claim 68, wherein the genomicintervals each comprise thousands to millions of base pairs.
 78. Thesystem of claim 68, wherein a cfDNA fragmentation profile is determinedwithin each genomic interval.
 79. The system of claim 68, wherein acfDNA fragmentation profile comprises a median fragment size.
 80. Thesystem of claim 68, wherein a cfDNA fragmentation profile comprises afragment size distribution.
 81. The system of claim 68, wherein a cfDNAfragmentation profile is determined over the whole genome or asubgenomic interval.
 82. The system of claim 68, wherein cfDNAfragmentation profiles provide over 20,000 reads per genomic intervals.83. The system of claim 68, wherein the genomic coverage is about 0.1×,0.2×, 0.5×, 1× or 2×.
 84. The system of claim 68, wherein the cfDNAfragmentation profile further predicts the tissue of origin of thecancer in a subject having or at risk of having cancer.
 85. The systemof claim 68, wherein the cancer is selected from the group consistingof: colorectal cancer, lung cancer, breast cancer, gastric cancer,pancreatic cancer, bile duct cancer, and ovarian cancer.
 86. The systemof claim 68, wherein the cancer is treated with or has previously beentreated with a treatment comprising administering to the subject acancer treatment selected from the group consisting of surgery, adjuvantchemotherapy, neoadjuvant chemotherapy, radiation therapy, hormonetherapy, cytotoxic therapy, immunotherapy, adoptive T cell therapy,targeted therapy and combination thereof.
 87. The system of claim 68,wherein cfDNA fragments are nucleosome protected DNA fragments.
 88. Thesystem of claim 68, wherein the sample is a blood, serum, plasma,amnion, tissue, urine, cerebrospinal fluid, saliva, sputum,broncho-alveolar lavage, bile, lymphatic fluid, cyst fluid, stool,ascites, pap smear, breast milk or exhaled breath condensate sample. 89.A method of predicting a cell free DNA (cfDNA) fragmentation profile ofa subject comprising: determining a cfDNA fragmentation profileprediction for the subject based on a DNA evaluation of fragments forearly interception (DELFI) classifier score, using the system of claim68, thereby predicting a cfDNA fragmentation profile of the subject. 90.A method of predicting a cancer status in a subject comprising:determining a cfDNA fragmentation profile prediction for the subjectusing the system of claim 68; and classifying the subject as a healthysubject or a subject having or at risk of having cancer based onvariability of the cfDNA fragmentation profile in the subject, therebypredicting a cancer status in the subject.
 91. A method of detectingand/or monitoring the status of cancer in a subject comprising:determining a first cfDNA fragmentation profile of the subject at afirst time using the system of claim 68; and classifying the subject asa healthy subject or a subject having or at risk of having cancer basedon the cfDNA fragmentation profile of the subject, thereby detectingcancer in the subject.
 92. The method of claim 91, further comprisingdetermining a second cfDNA fragmentation profile of the subject at asecond time and comparing the first cfDNA fragmentation profile to thesecond cfDNA fragmentation profile to monitor the status of cancer inthe subject.
 93. The method of claim 92, wherein the first and/or thesecond cfDNA fragmentation profiles are determined before, during and/orafter the course of a cancer treatment.
 94. The method of claim 93,wherein determining the first and/or the second cfDNA fragmentationprofiles over the course of a cancer treatment indicates responsivenessto the cancer treatment.
 95. The method of claim 92, wherein a secondcfDNA fragmentation profile that is less or equally variable than areference cfDNA fragmentation profile obtained in a healthy subjectindicates a response to the cancer treatment in the subject.
 96. Themethod of claim 92, wherein a second cfDNA fragmentation profile that ismore variable than a reference cfDNA fragmentation profile obtained in ahealthy subject indicates an absence of response to the cancer treatmentin the subject.
 97. The method of claim 91, wherein determining thecfDNA fragmentation profile is indicative of a change in tumor size,and/or change in tumor localization.